%% Added by Jason Digalakis @proceedings{DBLP:conf/icaisc/2008, editor = {Leszek Rutkowski and Ryszard Tadeusiewicz and Lotfi A. Zadeh and Jacek M. Zurada}, title = {Artificial Intelligence and Soft Computing - ICAISC 2008, 9th International Conference, Zakopane, Poland, June 22-26, 2008, Proceedings}, booktitle = {ICAISC}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, volume = {5097}, year = {2008}, isbn = {978-3-540-69572-1}, bibsource = {DBLP, http://dblp.uni-trier.de} } @inproceedings{DBLP:conf/ppsn/Esparcia-AlcazarMAPGSA08, author = {Anna Esparcia-Alc{\'a}zar and Ana I. Mart\'{\i}nez-Garc\'{\i}a and Jos{\'e} Miguel Albarrac\'{\i}n-Guillem and Marta E. Palmer-Gato and Juan Juli{\'a}n Merelo Guerv{\'o}s and Ken Sharman and Eva Alfaro-Cid}, title = {A Multiobjective Evolutionary Algorithm for the Linear Shelf Space Allocation Problem}, booktitle = {PPSN}, year = {2008}, pages = {1001-1010}, ee = {http://dx.doi.org/10.1007/978-3-540-87700-4_99}, crossref = {DBLP:conf/ppsn/2008}, bibsource = {DBLP, http://dblp.uni-trier.de} } @proceedings{DBLP:conf/ppsn/2008, editor = {G{\"u}nter Rudolph and Thomas Jansen and Simon M. Lucas and Carlo Poloni and Nicola Beume}, title = {Parallel Problem Solving from Nature - PPSN X, 10th International Conference Dortmund, Germany, September 13-17, 2008, Proceedings}, booktitle = {PPSN}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, volume = {5199}, year = {2008}, isbn = {978-3-540-87699-1}, bibsource = {DBLP, http://dblp.uni-trier.de} } @inproceedings{DBLP:conf/ppsn/RommermannEMGKK08, author = {Malte R{\"o}mmermann and Mark Edgington and Jan Hendrik Metzen and Jose de Gea and Yohannes Kassahun and Frank Kirchner}, title = {Learning Walking Patterns for Kinematically Complex Robots Using Evolution Strategies}, booktitle = {PPSN}, year = {2008}, pages = {1091-1100}, ee = {http://dx.doi.org/10.1007/978-3-540-87700-4_108}, crossref = {DBLP:conf/ppsn/2008}, bibsource = {DBLP, http://dblp.uni-trier.de} } @proceedings{DBLP:conf/ppsn/2008, editor = {G{\"u}nter Rudolph and Thomas Jansen and Simon M. Lucas and Carlo Poloni and Nicola Beume}, title = {Parallel Problem Solving from Nature - PPSN X, 10th International Conference Dortmund, Germany, September 13-17, 2008, Proceedings}, booktitle = {PPSN}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, volume = {5199}, year = {2008}, isbn = {978-3-540-87699-1}, bibsource = {DBLP, http://dblp.uni-trier.de} } @inproceedings{citeulike:895069, abstract = {This paper addresses the Microarray Gene Ordering problem. It consists in ordering a set of genes, grouping together the ones with similar behavior. This behavior can be measured as the gene’s activity level across a number of measurements. The Gene Ordering problem belongs to the NP-hard class and has strong implications in genetic and medical areas. The method employed is a Memetic Algorithm, which is a variant of the well known Genetic Algorithms. The algorithm employs several features like population structure, problem-specific crossover and mutation operators, local search, and parallel processing. The instances utilized are extracted from the literature and represent real systems with 106 up to 979 genes. The algorithm has a superior performance, successfully grouping the genes. Moreover, in this paper we evaluate the impact of parallel processing in the performance of the algorithm, especially for the larger instances, which required more computational effort.}, author = {Mendes, Alexandre and Cotta, Carlos and Garcia, Vin?cius and Franca, Paulo and Moscato, Pablo }, citeulike-article-id = {895069}, journal = {Proceedings of International Conference on Parallel Processing Workshops 2005 IEEE}, keywords = {algorithms memetic parallel}, priority = {2}, publisher = {IEEE Computer Society}, title = {Gene Ordering in Microarray Data Using Parallel Memetic Algorithms}, url = {http://ieeexplore.ieee.org/iel5/9965/32020/01488749.pdf}, year = {2005} } @article{horii99asynchronous, author = "Hirosuke Horii and Susumu Kunifuji and Teruo Matsuzawa", title = "Asynchronous Island Parallel {GA} Using Multiform Subpopulations", journal = "Lecture Notes in Computer Science", volume = "1585", pages = "122--129", year = "1999", url = "citeseer.nj.nec.com/208202.html" } @misc{ndez-experimental, author = "F. Fern?ndez and M. Tomassini and W.F. Punch and III and J.M. S?nchez", title = "Experimental Study of Multipopulation Parallel Genetic Programming.", url = "citeseer.nj.nec.com/445504.html" } @misc{ makinen97parallel, author = "R. Makinen and P. Neittaanmaki and J. Periaux and M. Sefrioui and J. Toivanen", title = "Parallel genetic solution for multiobjective mdo", text = "R. A. E. Makinen, P. Neittaanmaki, J. Periaux, M. Sefrioui, and J. Toivanen, `Parallel genetic solution for multiobjective mdo', in Parallel CFD'96, eds., A. Schiano, A. Ecer, J. Periaux, and N. Satofuka, pp. 352--459. Elsevier, (1997).", year = "1997", url = "citeseer.nj.nec.com/makinen97parallel.html" } @inproceedings{blesa01parallel, author = "Maria J. Blesa and Lluis Hernandez and Fatos Xhafa", title = "Parallel Skeletons for Tabu Search Method", booktitle = "{ICPADS}", pages = "23-30", year = "2001", url = "citeseer.nj.nec.com/blesa00parallel.html" } @misc{anp1erformance, author = "Vishal Aslot And", title = "Performance Characteristics of the SPEC OMP2001 Benchmarks", url = "citeseer.nj.nec.com/507455.html" } @misc{ll99study, author = "B. Ll", title = "A Study in Function Optimization with the Breeder Genetic Algorithm", text = "Belanche, Ll. A Study in Function Optimization with the Breeder Genetic Algorithm. LSI Research Report LSI-99-36-R. Universitat Polit`ecnica de Catalunya, 1999.", year = "1999", url = "citeseer.nj.nec.com/belanche99study.html" } @misc{inen-evolutionary, author = "Jari P. H?m?l?inen and Raino A.E. M?kinen and Pasi Tarvainen and Jari Toivanen", title = "Evolutionary Shape Optimization in CFD with Industrial Applications", url = "citeseer.nj.nec.com/515275.html" } @techreport{cappanera01local, author = "Paola {"}Cappanera and Marco{"} Trubian", title = "A local search based heuristic for the demand constrained multidimensional knapsack problem.", number = "TR-01-10", month = "01", year = "2001", url = "citeseer.nj.nec.com/459970.html" } @incollection{sbalzarini01microchannel, author = "Ivo F. Sbalzarini and Sibylle M{\"u}ller and Petros Koumoutsakos", title = "Microchannel {O}ptimization {U}sing {M}ultiobjective {E}volution {S}trategies", booktitle = "First International Conference on Evolutionary Multi-Criterion Optimization", publisher = "Springer-Verlag. Lecture Notes in Computer Science No. 1993", editor = "Eckart Zitzler and Kalyanmoy Deb and Lothar Thiele and Carlos A. Coello Coello and David Corne", pages = "516--530", year = "2001", url = "citeseer.nj.nec.com/444012.html" } @misc{sbalzarini-evolutionary, author = "Ivo F. Sbalzarini and Lester K. Su and P. Koumoutsakos", title = "Evolutionary optimization for flow experiments", url = "citeseer.nj.nec.com/sbalzarini00evolutionary.html" } @InProceedings{wakunda, author = {J{\"u}rgen Wakunda and Andreas Zell}, title = {Median-Selection for Parallel Steady-State Evolution Strategies}, booktitle = {Proceedings of the 6th Internation Conference "Parallel Problem Solving from Nature - PPSN VI}, year = {2000}, editor = {Marc Schoenauer and Kalyanmoy Deb and G{\"u}nther Rudolph and Xin Yao and Evelyne Lutton and Juan Julian Merelo and Hans-Paul Schwefel}, volume = {1917}, series = {Lecture Notes in Computer Science}, address = {Paris, Fance}, month = {September 16-20}, publisher = {Springer Verlag}, pages = {405--414}, url = {citeseer.nj.nec.com/wakunda00medianselection.html} } @inproceedings{wegener01theoretical, author = "Ingo Wegener", title = "Theoretical Aspects of Evolutionary Algorithms", booktitle = "Proceedings of {theTwenty}-EighthInternational Colloquium on Automata, Languages, and Programming({ICALP}\,2001)", month = "8 -- 12", address = "Crete, Greece", year = "2001", url = "citeseer.nj.nec.com/wegener01theoretical.html" } @inproceedings{wegener00design, author = "Ingo Wegener", title = "On the Design and Analysis of Evolutionary Algorithms", booktitle = "Proceedings of {theWorkshop} on Algorithm Engineering as a New Paradigm", pages = "36--47", year = "2000", url = "citeseer.nj.nec.com/wegener00design.html" } @inproceedings{alba99analysis, author = "Enrique Alba and Jose M. Troya", title = "An Analysis of Synchronous and Asynchronous Parallel Distributed Genetic Algorithms with Structured and Panmictic Islands", booktitle = "{IPPS}/{SPDP} Workshops", pages = "248-256", year = "1999", url = "citeseer.nj.nec.com/496233.html" } @inproceedings{raidl98improved, author = "G\"unther R. Raidl", title = "An Improved Memetic Algorithm for the Multiconstrained 0--1 Knapsack Problem", year = "1998", url = "citeseer.nj.nec.com/549619.html" } @inproceedings{sprave99unified, author = "Joachim Sprave", title = "A Unified Model of Non-Panmictic Population Structures in Evolutionary Algorithms", booktitle = "Proceedings of the Congress on Evolutionary Computation", volume = "2", month = "6-9", publisher = "IEEE Press", address = "Mayflower Hotel, Washington D.C., USA", editor = "Peter J. Angeline and Zbyszek Michalewicz and Marc Schoenauer and Xin Yao and Ali Zalzala", isbn = "0-7803-5537-7 (Microfiche)", pages = "1384--1391", year = "1999", url = "citeseer.nj.nec.com/sprave99unified.html" } @incollection{wegenerwegenermethods, author = "Ingo Wegener", title = "Methods for the Analysis of Evolutionary Algorithms on Pseudo-Boolean Functions", booktitle = "Evolutionary Optimization", publisher = "Kluwer Academic Publishers", address = "Dordrecht, The Netherlands", editor = "Ruhul Sarker and Masoud Mohammadian and Xin Yao", year = "2001, to appear", url = "citeseer.nj.nec.com/wegener00methods.html" } @misc{prabhu-behavior, author = "D. Prabhu and B.P. Buckles and F.E. Petry", title = "Behavior of Interconnected Subpopulations: Genetic Algorithms in a SIMD Environment", url = "citeseer.nj.nec.com/175274.html" } @techreport{abramson91parallel, author = "D. Abramson and J. Abela", title = "A Parallel Genetic Algorithm for Solving the School Timetabling Problem", year = "1991", url = "citeseer.nj.nec.com/abramson92parallel.html" } @misc{alander96indexed, author = "J. Alander", title = "An indexed bibliography of distributed genetic algorithms", text = "Jarmo T. Alander, An indexed bibliography of distributed genetic algorithms, Tech. Rep. No. 94-1-PARA, Univ. of Vaasa, Finland, 1996. ftp://ftp.uwasa.fi/cs/report94-1/gaPARAbib.ps.Z", year = "1996", url = "citeseer.nj.nec.com/article/alander99indexed.html" } @misc{arnold-with, author = "Jens Arnold and Peter K?chel and Holger Uhlig", title = "With Parallel Evolution towards the Optimal Order Policy of a Multi-Location Inventory with Lateral Transshipments", url = "citeseer.nj.nec.com/26256.html" } @misc{adamidis-parallel, author = "Panagiotis Adamidis", title = "Parallel Evolutionary Algorithms: A Review", url = "citeseer.nj.nec.com/17679.html" } @misc{ tz-application, author = "Martin Sch?tz and Joachim Sprave", title = "Application of Parallel Mixed-Integer Evolution Strategies with Mutation Rate Pooling", url = "citeseer.nj.nec.com/37817.html" } @misc{bachelet96parallel, author = "V. Bachelet and P. Preux and E. Talbi", title = "Parallel Hybrid Meta--Heuristics: Application to the Quadratic Assignment Problem", text = "V. Bachelet, P. Preux, and E.-G. Talbi, Parallel Hybrid Meta--Heuristics: Application to the Quadratic Assignment Problem, in Proceedings of the Parallel Optimization Colloquium, (Versailles, France), 1996.", year = "1996", url = "citeseer.nj.nec.com/bachelet96parallel.html" } @article{bachelet00parallel, author = "Vincent Bachelet and El-Ghazali Talbi", title = "A Parallel Co-evolutionary Metaheuristic", journal = "Lecture Notes in Computer Science", volume = "1800", pages = "628--??", year = "2000", url = "citeseer.nj.nec.com/bachelet00parallel.html" } @techreport{allenson92genetic, author = "Robin Allenson", title = "Genetic {A}lgorithms with {G}ender for {M}ulti-function {O}ptimisation", number = "EPCC-SS92-01", address = "Edinburgh, Scotland", year = "1992", url = "citeseer.nj.nec.com/allenson92genetic.html" } @misc{falco97introduction, author = "I. De Falco", title = "An introduction to Evolutionary Algorithms and their application to the Aerofoil Design Problem -- Part I: the Algorithms", text = "De Falco, I., 1997, An introduction to Evolutionary Algorithms and their application to the Aerofoil Design Problem -- Part I: the Algorithms, von Karman Lecture Series on Fluid Dynamics, Bruxelles, Belgium, April 1997.", year = "1997", url = "citeseer.nj.nec.com/defalco97introduction.html" } @misc{ yao96overview, author = "X. Yao", title = "An overview of evolutionary computation", text = "X. Yao, An overview of evolutionary computation, Chinese Journal of Advanced Software Research (Allerton Press, Inc., New York, NY 10011), vol. 3, no. 1, pp. 12--29, 1996.", year = "1996", url = "citeseer.nj.nec.com/yao96overview.html" } @misc{talbi-taxonomy, author = "E-G. Talbi", title = "A Taxonomy of Hybrid Metaheuristics", url = "citeseer.nj.nec.com/talbi99taxonomy.html" } @misc{beasley00population, author = "J. Beasley", title = "Population heuristics", text = "J.E. Beasley, Population heuristics, forthcoming in Handbook of applied optimization, P.M. Pardalos and M.G.C. Resende (eds). Oxford University Press (2000).", year = "2000", url = "citeseer.nj.nec.com/beasley99population.html" } @BOOK {Aarts1989, AUTHOR = {Emile Aarts and Jan Korst}, TITLE = {Simulated Annealing and Boltzmann Machines: A Stochastic Approach to Combinatorial Optimization and Neural Computing}, PUBLISHER = {John Wiley \& Sons}, ADDRESS = {Chichester}, YEAR = {1989}, VOLUME = {}, SERIES = {Wiley Interscience Series in Discrete Mathematics and Optimization}, EDITION = {}, MONTH = {}, NOTE = {} } @inproceedings{kliewer2000c, author = {Georg Kliewer and Stefan Tsch?ke}, title = {A General Parallel Simulated Annealing Library and Its Application in Airline Industry}, booktitle = {Proceedings of the 14th International Parallel and Distributed Processing Symposium (IPDPS 2000)}, pages = {55--61}, year = {2000}, address = {Cancun, Mexico}, OPTmonth = {May}, organization = {IEEE}, url = {citeseer.nj.nec.com/kliewer00general.html} } @article{ruizandino98parallel, author = "Alvaro Ruiz-Andino and Lourdes Araujo and Jose Ruz and Fernando S{\'a}enz", title = "Parallel Evolutionary Optimisation with Constraint Propagation", journal = "Lecture Notes in Computer Science", volume = "1498", pages = "270--??", year = "1998", url = "citeseer.nj.nec.com/262662.html" } @inproceedings{merz99comparison, author = "Peter Merz and Bernd Freisleben", title = "A Comparison of Memetic Algorithms, Tabu Search, and Ant Colonies for the Quadratic Assignment Problem", booktitle = "Proceedings of the Congress on Evolutionary Computation", volume = "3", month = "6-9", publisher = "IEEE Press", address = "Mayflower Hotel, Washington D.C., USA", editor = "Peter J. Angeline and Zbyszek Michalewicz and Marc Schoenauer and Xin Yao and Ali Zalzala", isbn = "0-7803-5537-7 (Microfiche)", pages = "2063--2070", year = "1999", url = "citeseer.nj.nec.com/merz99comparison.html" } @misc{estivillcastrohow, author = "Vladimir Estivill-Castro and Rodolfo Torres-Vel?zquez", title = "How should feasibility be handled by Genetic Algorithms on Constraint Combinatorial Optimization Problems? The case of the valued n-queens problem", url = "citeseer.nj.nec.com/442569.html" } @inproceedings{kliewer2000b, author = {Georg Kliewer}, title = {A General Software Library for Parallel Simulated Annealing}, booktitle = {EURO Winter Institute on Metaheuristics in Combinatorial Optimisation}, year = {2000}, address = {Lac Noir, Switzerland}, OPTmonth = {March}, note = {Submitted to the European Journal of Operational Research (EJOR)}, url = {citeseer.nj.nec.com/article/kliewer00general.html} } @misc{andtopologies, author = "Merrill And", title = "Topologies, Proc. of Parallel Problem Solving from Nature, Schwefel H.P. and Maenner R. (Eds.), pp. 274--283, Lect. Notes in Computer Science, Springer", url = "citeseer.nj.nec.com/13182.html" } @misc{xing96parallel, author = "Z. Xing and P. Banerjee", title = "A Parallel Hierarchical Algorithm for Module Placement Based on Sparse Linear Equations", text = "Z. Xing and P. Banerjee, A Parallel Hierarchical Algorithm for Module Placement Based on Sparse Linear Equations, UIUC-CRHC Technical Report, 1996.", year = "1996", url = "citeseer.nj.nec.com/xing96parallel.html" } @article{ babaoglu01group, author = "Ozalp Babaoglu and Renzo Davoli and Alberto Montresor", title = "Group Communication in Partitionable Systems: Specification and Algorithms", journal = "Software Engineering", volume = "27", number = "4", pages = "308-336", year = "2001", url = "citeseer.nj.nec.com/babaoglu98group.html" } @misc{duvivier95parallel, author = "D. Duvivier and P. Preux and E. Talbi", title = "Parallel genetic algorithms for optimization and application to NP-complete problem solving in Int", text = "D. Duvivier and P. Preux and E. G. Talbi, Parallel genetic algorithms for optimization and application to NP-complete problem solving in Int. Workshop on Combinatorics and Computer Science, Brest, France, 1995", year = "1995", url = "citeseer.nj.nec.com/duvivier95parallel.html" } @BOOK {Ackley1987, AUTHOR = {David H. Ackley}, TITLE = {A Connectionist Machine for Genetic Hillclimbing}, PUBLISHER = {Kluwer Academic Publishers}, ADDRESS = {Boston}, YEAR = {1987}, VOLUME = {SECS28}, SERIES = {The Kluwer International Series in Engineering and Computer Science.}, EDITION = {}, MONTH = {}, NOTE = {}, SIGNATURE = {WU, Janko, 1557/I.2} } @PROCEEDINGS{Albrecht1993, EDITOR = {Rudolf F. Albrecht and Nigel C. Steele and Colin R. Reeves}, BOOKTITLE = {Artificial Neural Nets and Genetic Algorithms}, TITLE = {Artificial Neural Nets and Genetic Algorithms}, YEAR = {1993}, MONTH = {}, VOLUME = {}, NUMBER = {}, SERIES = {}, ORGANISATION = {Institut f\"ur Informatik, Universit\"at Innsbruck}, PUBLISHER = {Springer Verlag}, ADDRESS = {Wien}, NOTE = {}, SIGNATURE = {Extraordinariat Panny, 318E/I.2} } @INPROCEEDINGS{Garigliano1993, CROSSREF = {Albrecht1993}, AUTHOR = {R. Garigliano and A. Purvis and P. A. Giles and D. J. Nettleton}, TITLE = {An Adaptive Plan}, PAGES = {331--337}, } @INPROCEEDINGS{DeFalco1993, CROSSREF = {Albrecht1993}, AUTHOR = {I. DeFalco and R. DelBalio and E. Tarantino and R. Vaccaro}, TITLE = {Mapping Parallel Genetic Algorithms on WK-Recursive Topologies}, PAGES = {338--343}, } @INPROCEEDINGS{Reeves1993a, CROSSREF = {Albrecht1993}, AUTHOR = {C. R. Reeves}, TITLE = {Diversity and Diversification in Genetic Algorithms: Some Connections with Tabu Search}, PAGES = {344--351}, } %%% added by Jason end @INPROCEEDINGS{Snyers1993, CROSSREF = {Albrecht1993}, AUTHOR = {D. Snyers}, TITLE = {Clique Partitioning Problem and Genetic Algorithms}, PAGES = {352--360}, } @INPROCEEDINGS{Ono1993, CROSSREF = {Albrecht1993}, AUTHOR = {N. Ono and A. T. Rahmani}, TITLE = {Self-Organization of Communication in Distributed Learning Classifier Systems}, PAGES = {361--367}, } @INPROCEEDINGS{Goerne1993, CROSSREF = {Albrecht1993}, AUTHOR = {T. G{\"o}rne and M. Schneider}, TITLE = {Design of Digital Filters with Evolutionary Algorithms}, PAGES = {368--374}, } @INPROCEEDINGS{Autere1993, CROSSREF = {Albrecht1993}, AUTHOR = {A. Autere}, TITLE = {An Empirical Study of Population and Non-Population Based Search Strategies for Optimizing a Combinatorial Problem}, PAGES = {375--384}, } @INPROCEEDINGS{Tomassini1993, CROSSREF = {Albrecht1993}, AUTHOR = {M. Tomassini}, TITLE = {The Parallel Genetic Cellular Automata: Application to Global Function Optimization}, PAGES = {385--391}, } @INPROCEEDINGS{Freisleben1993, CROSSREF = {Albrecht1993}, AUTHOR = {B. Freisleben and M. H{\"a}rtfelder}, TITLE = {Optimization of Genetic Algorithms by Genetic Algorithms}, PAGES = {392--399}, } @INPROCEEDINGS{Deugo1993, CROSSREF = {Albrecht1993}, AUTHOR = {D. Deugo and F. Oppacher}, TITLE = {Achieving Self-Stabilization in a Distributed System Using Evolutionary Strategies}, PAGES = {400--407}, } @INPROCEEDINGS{Fairley1993, CROSSREF = {Albrecht1993}, AUTHOR = {A. Fairley and D. F. Yates}, TITLE = {Improving Simple Classifier Systems to Alleviate the Problems of Duplication, Subsumption and Equivalence of Rules}, PAGES = {408--416}, } @INPROCEEDINGS{Gaborski1993, CROSSREF = {Albrecht1993}, AUTHOR = {R. S. Gaborski and P. G. Anderson and D. Tilley and C. T. Ashbury}, TITLE = {Genetic Algorithm Selection of Features for Hand--Printed Character Recognition}, PAGES = {417--422}, } @INPROCEEDINGS{Cucchiara1993, CROSSREF = {Albrecht1993}, AUTHOR = {R. Cucchiara}, TITLE = {Analysis and Comparison of Different Genetic Models for the Clustering Problem in Image Analysis}, PAGES = {423--427}, } @INPROCEEDINGS{Cliff1993, CROSSREF = {Albrecht1993}, AUTHOR = {D. T. Cliff and P. Husbands and I. Harvey}, TITLE = {Evolving Recurrent Dynamical Networks for Robot Control}, PAGES = {428--435}, } @INPROCEEDINGS{Warwick1993, CROSSREF = {Albrecht1993}, AUTHOR = {K. Warwick and Y. H. Kang}, TITLE = {Genetic Algorithms for On-Line System Identification}, PAGES = {436--440}, } @INPROCEEDINGS{DeGaris1993, CROSSREF = {Albrecht1993}, AUTHOR = {H. DeGaris}, TITLE = {Evolvable Hardware Genetic Programming of a Darwin Machine}, PAGES = {441--449}, } @INPROCEEDINGS{Yin1993a, CROSSREF = {Albrecht1993}, AUTHOR = {X. Yin and N. Germay}, TITLE = {A Fast Genetic Algorithm with Sharing Scheme Using Cluster Analysis Methods in Multimodal Function Optimization}, PAGES = {450--457}, } @INPROCEEDINGS{Filipic1993, CROSSREF = {Albrecht1993}, AUTHOR = {B. Filipic and D. Juricic}, TITLE = {An Interactive Genetic Algorithm for Controller Parameter Optimization}, PAGES = {458--462}, } @INPROCEEDINGS{Biondi1993, CROSSREF = {Albrecht1993}, AUTHOR = {J. Biondi}, TITLE = {Robustness and Evolution in an Adaptive System Application on Classification Task}, PAGES = {463--470}, } @INPROCEEDINGS{Alander1993, CROSSREF = {Albrecht1993}, AUTHOR = {J. T. Alander}, TITLE = {On Robot Navigation Using a Genetic Algorithm}, PAGES = {471--478}, } @INPROCEEDINGS{Carbonaro1993, CROSSREF = {Albrecht1993}, AUTHOR = {A. Carbonaro and G. Casadei and A. Palareti}, TITLE = {Genetic Algorithms and Classifier Systems in Simulating a Cooperative Behavior}, PAGES = {479--483}, } @INPROCEEDINGS{Escazut1993, CROSSREF = {Albrecht1993}, AUTHOR = {C. Escazut and P. Collard and J.-L. Cavarero}, TITLE = {Dynamic Management of the Specificity in Classifier Systems}, PAGES = {484--491}, } @INPROCEEDINGS{Beaty1993, CROSSREF = {Albrecht1993}, AUTHOR = {S. J. Beaty}, TITLE = {Genetic Algorithms Versus Tabu Search for Instruction Scheduling}, PAGES = {496--501}, } @INPROCEEDINGS{Schwehm1993, CROSSREF = {Albrecht1993}, AUTHOR = {M. Schwehm}, TITLE = {A Massively Parallel Genetic Algorithm on the {M}as{P}ar {M}{P} 1}, PAGES = {502--507}, } @INPROCEEDINGS{Bassett1993, CROSSREF = {Albrecht1993}, AUTHOR = {S. Bassett and M. Winchell}, TITLE = {Standard Cell Routing Optimization Using a Genetic Algorithm}, PAGES = {508--514}, } @INPROCEEDINGS{Hartmann1993, CROSSREF = {Albrecht1993}, AUTHOR = {U. Hartmann}, TITLE = {Efficient Parallel Learning in Classifier Systems}, PAGES = {515--521}, } @INPROCEEDINGS{Bull1993, CROSSREF = {Albrecht1993}, AUTHOR = {L. Bull and T. C. Fogarty}, TITLE = {Co-evolving Communicating Classifier Systems for Tracking}, PAGES = {522--527}, } @INPROCEEDINGS{Sandqvist1993, CROSSREF = {Albrecht1993}, AUTHOR = {S. Sandqvist}, TITLE = {On Finding Optimal Potential Customers from a Large Marketing Database -- A Genetic Algorithm Approach}, PAGES = {528--535}, } @INPROCEEDINGS{Keane1993, CROSSREF = {Albrecht1993}, AUTHOR = {A. J. Keane}, TITLE = {Structural Design for Enhanced Noise Performance Using Genetic Algorithms and Other Optimization Techniques}, PAGES = {536--543}, } @INPROCEEDINGS{Parmee1993, CROSSREF = {Albrecht1993}, AUTHOR = {I. Parmee}, TITLE = {The Concrete Arch Dam, an Evolutionary Model of the Design Process}, PAGES = {544--551}, } @INPROCEEDINGS{Walker1993, CROSSREF = {Albrecht1993}, AUTHOR = {J. D. Walker and P. E. File and C. J. Miller and W. B. Samson}, TITLE = {The GENIE Project - A Genetic Algorithm Application to a Sequencing Problem in the Biological Domain}, PAGES = {552--558}, } @INPROCEEDINGS{Prinetto1993, CROSSREF = {Albrecht1993}, AUTHOR = {P. Prinetto and M. Rebaudengo and M. Sonza Reorda}, TITLE = {Hybrid Genetic Algorithms for the Traveling Salesman Problem}, PAGES = {559--566}, } @INPROCEEDINGS{Berry1993, CROSSREF = {Albrecht1993}, AUTHOR = {R. H. Berry and G. D. Smith}, TITLE = {Using a Genetic Algorithm to Investigate Taxation Induced Interactions in Capital Budgeting}, PAGES = {567--574}, } @INPROCEEDINGS{Kapsalis1993, CROSSREF = {Albrecht1993}, AUTHOR = {A. Kapsalis and V. J. Rayward-Smith and G. D. Smith}, TITLE = {Fast Sequential and Parallel Implementation of Genetic Algorithms Using the {G}{A}meter Toolkit}, PAGES = {575--582}, } @INPROCEEDINGS{Hindi1993, CROSSREF = {Albrecht1993}, AUTHOR = {K. S. Hindi and Y. M. Hamam}, TITLE = {Locating Pressure Control Elements for Leakage Minimisation in Water Supply Networks by Genetic Algorithms}, PAGES = {583--587}, } @INPROCEEDINGS{Miglino1993, CROSSREF = {Albrecht1993}, AUTHOR = {O. Miglino and R. Pedone and D. Parisi}, TITLE = {A `Noise Gene' for Econets}, PAGES = {588--594}, } @INPROCEEDINGS{Lange1993, CROSSREF = {Albrecht1993}, AUTHOR = {B. Lange and C. Hornung}, TITLE = {A Solution to Global Illumination by Recursive Genetic Algorithms}, PAGES = {595--601}, } @INPROCEEDINGS{Jakob1993, CROSSREF = {Albrecht1993}, AUTHOR = {C. Jakob and A. Burghof}, TITLE = {{N}e{X}{T}{G}ene: A Graphical User-Interface under {G}{E}{N}{E}{S}{I}{S} under {N}e{X}{T}{S}tep}, PAGES = {602--606}, } @INPROCEEDINGS{Stender1993, CROSSREF = {Albrecht1993}, AUTHOR = {J. Stender and K. Tout and P. Stender}, TITLE = {Using Genetic Algorithms in Economic Modelling: The Many-Agents Approach}, PAGES = {607--612}, } @INPROCEEDINGS{Hoefferer1993, CROSSREF = {Albrecht1993}, AUTHOR = {M. Hoefferer}, TITLE = {{G}{I}{R}{S}: A Genetic Approach to Information Retrieval}, PAGES = {613--619}, } @INPROCEEDINGS{Casadei1993, CROSSREF = {Albrecht1993}, AUTHOR = {G. Casadei and A. Palareti and G. Proli}, TITLE = {Classifier System in Traffic Management}, PAGES = {620--627}, } @INPROCEEDINGS{Munro1993, CROSSREF = {Albrecht1993}, AUTHOR = {P. Munro}, TITLE = {Genetic Search for Optimal Representations in Neural Networks}, PAGES = {628--634}, } @INPROCEEDINGS{Maniezzo1993, CROSSREF = {Albrecht1993}, AUTHOR = {V. Maniezzo}, TITLE = {Searching Among Search Spaces: Hastening the Genetic Evolution of Feedforward Neural Networks}, PAGES = {635--642}, } @INPROCEEDINGS{Mandischer1993, CROSSREF = {Albrecht1993}, AUTHOR = {M. Mandischer}, TITLE = {Representation and Evolution of Neural Networks}, PAGES = {643--649}, } @INPROCEEDINGS{Philipsen1993, CROSSREF = {Albrecht1993}, AUTHOR = {W.J.M. Philipsen and L.J.M. Cluitmans}, TITLE = {Using a Genetic Algorithm to Tune Potts Neural Networks}, PAGES = {650--657}, } @INPROCEEDINGS{Thierens1993a, CROSSREF = {Albrecht1993}, AUTHOR = {D. Thierens and J. Suykens and J. Vandewalle and B. DeNoor}, TITLE = {Genetic Weight Optimization of a Feedforward Neural Network Controller}, PAGES = {658--663}, } @INPROCEEDINGS{Mitchell1993, CROSSREF = {Albrecht1993}, AUTHOR = {R. J. Mitchell and J. M. Bishop and W. Low}, TITLE = {Using a Genetic Algorithm to Find the Rules of a Neural Network}, PAGES = {664--669}, } @INPROCEEDINGS{Arena1993, CROSSREF = {Albrecht1993}, AUTHOR = {P. Arena and R. Caponetti and I. Fortuna and M. G. Xibilia}, TITLE = {{M}{L}{P} Optimal Topology via Genetic Algorithms}, PAGES = {670--674}, } @INPROCEEDINGS{Schiffmann1993, CROSSREF = {Albrecht1993}, AUTHOR = {W. Schiffmann and M. Joost and R. Werner}, TITLE = {Application of Genetic Algorithms to the Construction of Topologies for Multilayer Perceptrons}, PAGES = {675--682}, } @INPROCEEDINGS{Alba1993, CROSSREF = {Albrecht1993}, AUTHOR = {E. Alba and J. F. Aldana and J. M. Troya}, TITLE = {Genetic Algorithms as Heuristics for Optimizing ANN Design}, PAGES = {683--690}, } @INPROCEEDINGS{Fekadu1993, CROSSREF = {Albrecht1993}, AUTHOR = {A. Fekadu and E. L. Hines and J. W. Gardner}, TITLE = {Genetic Algorithm Design of Neural Net Based Electronic Nose}, PAGES = {691--698}, } @INPROCEEDINGS{DeGaris1993a, CROSSREF = {Albrecht1993}, AUTHOR = {H. DeGaris}, TITLE = {Circuits of Production Rule {G}en{N}ets. {T}he Genetic Programming of Artificial Nervous Systems}, PAGES = {699--705}, } @INPROCEEDINGS{Kwiatkowski1993, CROSSREF = {Albrecht1993}, AUTHOR = {L. Kwiatkowski and J. P. Stromboni}, TITLE = {Neuromimetic Algorithms Processing: Tools for Design of Dedicated Architectures}, PAGES = {706--711}, } @INPROCEEDINGS{Ball1993, CROSSREF = {Albrecht1993}, AUTHOR = {N. R. Ball}, TITLE = {Towards the Development of Cognitive Maps in Classifier Systems}, PAGES = {712--718}, } @INPROCEEDINGS{Bishop1993, CROSSREF = {Albrecht1993}, AUTHOR = {J. M. Bishop and M. J. Bushnell and A. Usher and S. Westland}, TITLE = {Genetic Optimization of Neural Network Architectures for Colour Recipe Prediction}, PAGES = {719--725}, } @INPROCEEDINGS{Robbins1993, CROSSREF = {Albrecht1993}, AUTHOR = {P. Robbins and A. Soper and K. Rennols}, TITLE = {Use of Genetic Algorithms for Optimal Topology Determination in Back Propagation Neural Networks}, PAGES = {726--730}, } @INPROCEEDINGS{Fielder1993, CROSSREF = {Albrecht1993}, AUTHOR = {D. Fielder and C. O. Alford}, TITLE = {Counting and Naming Connection Islands on a Grid of Conductors}, PAGES = {731--737}, } @BOOK {Bauer1994, AUTHOR = {Richard J. Bauer}, TITLE = {Genetic Algorithms and Investment Strategies}, PUBLISHER = {John Wiley \& Sons}, ADDRESS = {New York}, YEAR = {1994}, VOLUME = {}, SERIES = {Wiley Finance Editions}, EDITION = {}, MONTH = {}, NOTE = {} } @PROCEEDINGS{Belew1991, EDITOR = {Richard K. Belew and Lashon B. Booker}, BOOKTITLE = {Proceedings of the Fourth International Conference on Genetic Algorithms}, TITLE = {Proceedings of the Fourth International Conference on Genetic Algorithms (ICGA'91)}, YEAR = {1991}, MONTH = {}, VOLUME = {}, NUMBER = {}, SERIES = {}, ORGANISATION = {University of California, San Diego}, PUBLISHER = {Morgan Kaufmann Publishers}, ADDRESS = {San Mateo, California}, NOTE = {}, SIGNATURE = {WU, Panny, 221E/I.2} } @INPROCEEDINGS{Baeck1991a, CROSSREF = {Belew1991}, AUTHOR = {T. B{\"a}ck and F. Hoffmeister and H.-P. Schwefel}, TITLE = {A Survey of Evolution Strategies}, PAGES = {2--9}, } @INPROCEEDINGS{Bagchi1991, CROSSREF = {Belew1991}, AUTHOR = {Sugato Bagchi and Serdar Uckun and Yutaka Miyabe and Kazuhiko Kawamura}, TITLE = {Exploring Problem-Specific Recombination Operators for Job Shop Scheduling}, PAGES = {10--17}, } @INPROCEEDINGS{Davis1991a, CROSSREF = {Belew1991}, AUTHOR = {Lawrence Davis}, TITLE = {Bit-Climbing, Representational Bias, and Test Suite Design}, PAGES = {18--23}, } @INPROCEEDINGS{Goldberg1991, CROSSREF = {Belew1991}, AUTHOR = {David E. Goldberg and Kalyanmoy Deb and Bradley Korb}, TITLE = {Don't Worry, Be Messy}, PAGES = {24--30}, } @INPROCEEDINGS{Janikow1991, CROSSREF = {Belew1991}, AUTHOR = {Cezary Z. Janikow and Zbigniew Michalwicz}, TITLE = {An Experimental Comparison of Binary and Floating Point Representations in Genetic Algorithms}, PAGES = {31--36}, } @INPROCEEDINGS{Koza1991, CROSSREF = {Belew1991}, AUTHOR = {John R. Koza}, TITLE = {Evolving a Computer Program to Generate Random Numbers Using the Genetic Programming Paradigm}, PAGES = {37--44}, } @INPROCEEDINGS{Laszewski1991, CROSSREF = {Belew1991}, AUTHOR = {Gregor von Laszewski}, TITLE = {Intelligent Structural Operators for the k-way Graph Partitioning Problem}, PAGES = {45--52}, } @INPROCEEDINGS{Louis1991, CROSSREF = {Belew1991}, AUTHOR = {Sushil J. Louis and Gregory J.E. Rawlins}, TITLE = {Designer Genetic Algorithms: Genetic Algorithms in Structure Design}, PAGES = {53--60}, } @INPROCEEDINGS{Schaffer1991, CROSSREF = {Belew1991}, AUTHOR = {J. David Schaffer and Larry J. Eshelman}, TITLE = {On Crossover as an Evolutionary Viable Strategy}, PAGES = {61--68}, } @INPROCEEDINGS{Starkweather1991, CROSSREF = {Belew1991}, AUTHOR = {T. Starkweather and S. McDaniel and K. Mathias and D. Whitley and C. Whitley}, TITLE = {A Comparison of Genetic Sequencing Operators}, PAGES = {69--76}, } @INPROCEEDINGS{Whitley1991, CROSSREF = {Belew1991}, AUTHOR = {D. Whitley and K. Mathias and P. Fitzhorn}, TITLE = {Delta Coding: An Iterative Search Strategy for Genetic Algorithms}, PAGES = {77--84}, } @INPROCEEDINGS{Wilson1991, CROSSREF = {Belew1991}, AUTHOR = {Stewart W. Wilson}, TITLE = {GA-Easy Does Not Imply Steepest Ascent Optimizable}, PAGES = {85--91}, } @INPROCEEDINGS{Baeck1991b, CROSSREF = {Belew1991}, AUTHOR = {Thomas B{\"a}ck and Frank Hoffmeister}, TITLE = {Extended Selection Mechanisms in Genetic Algorithms}, PAGES = {92--99}, } @INPROCEEDINGS{Bramlette1991, CROSSREF = {Belew1991}, AUTHOR = {Mark F. Bramlette}, TITLE = {Initialization, Mutation and Selection Methods in Genetic Algorithms for Function Optimization}, PAGES = {100--107}, } @INPROCEEDINGS{Cartwright1991, CROSSREF = {Belew1991}, AUTHOR = {Hugh M. Cartwright and Gregory F. Mott}, TITLE = {Looking Around: Using Clues from the Data Space to Guide Genetic Algorithm Searches}, PAGES = {108--114}, } @INPROCEEDINGS{Eshelman1991, CROSSREF = {Belew1991}, AUTHOR = {Larry J. Eshelman and David J. Schaffer}, TITLE = {Preventing Premature Convergence in Genetic Algorithms by Preventing Incest}, PAGES = {115--122}, } @INPROCEEDINGS{Levenick1991, CROSSREF = {Belew1991}, AUTHOR = {James R. Levenick}, TITLE = {Inserting Introns Improves Genetic Algorithm Success Rate: Taking a Cue from Biology}, PAGES = {123--127}, } @INPROCEEDINGS{Lipsitch1991, CROSSREF = {Belew1991}, AUTHOR = {Marc Lipsitch}, TITLE = {Adaptation on Rugged Landscapes Generated by Iterated Local Interactions of Neighboring Genes}, PAGES = {128--135}, } @INPROCEEDINGS{Littman1991, CROSSREF = {Belew1991}, AUTHOR = {Michael L. Littman and David H. Ackley}, TITLE = {Adaptation in Constant Utility Non-Stationary Environments}, PAGES = {136--142}, } @INPROCEEDINGS{Manderick1991, CROSSREF = {Belew1991}, AUTHOR = {Bernard Manderick and Mark de Weger and Piet Spiessens}, TITLE = {The Genetic Algorithm and the Structure of the Fitness Landscape}, PAGES = {143--150}, } @INPROCEEDINGS{Michalewicz1991, CROSSREF = {Belew1991}, AUTHOR = {Zbigniew Michalewicz and Cezary Z. Janikow}, TITLE = {Handling Constraints in Genetic Algorithms}, PAGES = {151--157}, } @INPROCEEDINGS{Schultz1991, CROSSREF = {Belew1991}, AUTHOR = {Alan C. Schultz}, TITLE = {Adapting the Evaluation Space to Improve Global Learning}, PAGES = {158--165}, } @INPROCEEDINGS{Das1991, CROSSREF = {Belew1991}, AUTHOR = {Rajarshi Das and Darrell Whitley}, TITLE = {The Only Challenging Problems are Deceptive: Global Search by Solving Order-1 Hyperplanes}, PAGES = {166--173}, } @INPROCEEDINGS{TDavis1991, CROSSREF = {Belew1991}, AUTHOR = {Thomas E. Davis and Jose C. Principe}, TITLE = {A Simulated Annealing Like Convergence Theory for the Simple Genetic Algorithm}, PAGES = {174--181}, } @INPROCEEDINGS{Forrest1991, CROSSREF = {Belew1991}, AUTHOR = {Stephanie Forrest and Melanie Mitchell}, TITLE = {The Performance of Genetic Algorithms on {W}alsh Polynomials: Some Anomalous Results and Their Explanation}, PAGES = {182--189}, } @INPROCEEDINGS{Hart1991, CROSSREF = {Belew1991}, AUTHOR = {William E. Hart and Richard K. Belew}, TITLE = {Optimizing an Arbitrary Function is Hard for the Genetic Algorithm}, PAGES = {190--195}, } @INPROCEEDINGS{Homaifar1991, CROSSREF = {Belew1991}, AUTHOR = {Abdollah Homaifar and Xiaoyun Qi and John Fost}, TITLE = {Analysis and Design of General GA Deceptive Problem}, PAGES = {196--203}, } @INPROCEEDINGS{Hulin1991a, CROSSREF = {Belew1991}, AUTHOR = {Martin Hulin}, TITLE = {Analysis of Schema Distributions}, PAGES = {204--209}, } @INPROCEEDINGS{Mason1991, CROSSREF = {Belew1991}, AUTHOR = {Andrew J. Mason}, TITLE = {Partition Coefficients, Static Deception and Deceptive Problems for Non-Binary Alphabets}, PAGES = {210--214}, } @INPROCEEDINGS{Rabinovich1991, CROSSREF = {Belew1991}, AUTHOR = {Yuri Rabinovich and Avi Wigderson}, TITLE = {An Analysis of a Simple Genetic Algorithm}, PAGES = {215--221}, } @INPROCEEDINGS{Radcliffe1991, CROSSREF = {Belew1991}, AUTHOR = {Nicholas J. Radcliffe}, TITLE = {Forma Analysis and Random Respectful Recombination}, PAGES = {222--229}, } @INPROCEEDINGS{Spears1991, CROSSREF = {Belew1991}, AUTHOR = {William M. Spears and Kenneth A. DeJong}, TITLE = {On the Virtues of Parametrized Uniform Crossover}, PAGES = {230--236}, } @INPROCEEDINGS{Vose1991, CROSSREF = {Belew1991}, AUTHOR = {Michael D. Vose and Gunar E. Liepins}, TITLE = {Schema Disruptions}, PAGES = {237--243}, } @INPROCEEDINGS{Cohoon1991, CROSSREF = {Belew1991}, AUTHOR = {J. P. Cohoon and W. N. Martin and D. S. Richards}, TITLE = {A Multi-Population Genetic Algorithm for Solving the K-Partition Problem on Hyper-Cubes}, PAGES = {244--248}, } @INPROCEEDINGS{Collins1991, CROSSREF = {Belew1991}, AUTHOR = {Robert J. Collins and David R. Jefferson}, TITLE = {Selection in Massively Parallel Genetic Algorithms}, PAGES = {249--256}, } @INPROCEEDINGS{Davidor1991, CROSSREF = {Belew1991}, AUTHOR = {Yuval Davidor}, TITLE = {A Naturally Occuring Niche \& Species Phenomenon: The Model and First Results}, PAGES = {257--263}, } @INPROCEEDINGS{Husbands1991a, CROSSREF = {Belew1991}, AUTHOR = {Philip Husbands and Frank Mill}, TITLE = {Simulated Co-Evolution as the Mechanism for Emergent Planning and Scheduling}, PAGES = {264--270}, } @INPROCEEDINGS{Muehlenbein1991, CROSSREF = {Belew1991}, AUTHOR = {H. M{\"u}hlenbein and M. Schomisch and J. Born}, TITLE = {The Parallel Genetic Algorithm as Function Optimizer}, PAGES = {271--278}, } @INPROCEEDINGS{Spiessens1991, CROSSREF = {Belew1991}, AUTHOR = {Piet Spiessens and Bernard Manderick}, TITLE = {A Massively Parallel Genetic Algorithm: Implementation and First Analysis}, PAGES = {279--287}, } @INPROCEEDINGS{Bonelli1991, CROSSREF = {Belew1991}, AUTHOR = {Pierre Bonelli and Alexandre Parodi}, TITLE = {An Efficient Classifier System and Its Experimental Comparison with Two Representative Learning Methods on Three Medical Domains}, PAGES = {288--295}, } @INPROCEEDINGS{Dorigo1991, CROSSREF = {Belew1991}, AUTHOR = {Marco Dorigo and Enrico Sirtori}, TITLE = {Alecsys: A Parallel Laboratory for Learning Classifier Systems}, PAGES = {296--302}, } @INPROCEEDINGS{Grefenstette1991, CROSSREF = {Belew1991}, AUTHOR = {John J. Grefenstette}, TITLE = {Lamarckian Learning in Multi-Agent Environments}, PAGES = {303--310}, } @INPROCEEDINGS{Kitano1991, CROSSREF = {Belew1991}, AUTHOR = {Hiroaki Kitano and Stephen F. Smith and Tetsuya Higuchi}, TITLE = {GA-1: A Parallel Associative Memory Processor for Rule Learning with Genetic Algorithms}, PAGES = {311--317}, } @INPROCEEDINGS{Liepins1991, CROSSREF = {Belew1991}, AUTHOR = {Gunar E. Liepins and Lori A. Wang}, TITLE = {Classifier System Learning of Boolean Concepts}, PAGES = {318--323}, } @INPROCEEDINGS{Riolo1991, CROSSREF = {Belew1991}, AUTHOR = {Rick L. Riolo}, TITLE = {Modeling Simple Human Category Learning with a Classifier System}, PAGES = {324--333}, } @INPROCEEDINGS{Sedbrook1991, CROSSREF = {Belew1991}, AUTHOR = {Tod A. Sedbrook and Haviland Wright and Richard Wright}, TITLE = {Application of a Genetic Classifier System for Patient Triage}, PAGES = {334--338}, } @INPROCEEDINGS{Shu1991, CROSSREF = {Belew1991}, AUTHOR = {Lingyan Shu and Jonathan Schaeffer}, TITLE = {HCS: Adding Hierarchies to Classifier Systems}, PAGES = {339--345}, } @INPROCEEDINGS{Rendon1991, CROSSREF = {Belew1991}, AUTHOR = {Manuel Valenzuela-Rend{\'o}n}, TITLE = {The Fuzzy Classifier System: A Classifier System for Continuously Varying Variables}, PAGES = {346--353}, } @INPROCEEDINGS{Westerdale1991, CROSSREF = {Belew1991}, AUTHOR = {T. H. Westerdale}, TITLE = {Redundant Classifiers and Prokaryote Genomes}, PAGES = {354--361}, } @INPROCEEDINGS{Bhanu1991, CROSSREF = {Belew1991}, AUTHOR = {Bir Bhanu and Sungkee Lee and John Ming}, TITLE = {Self-Optimizing Image Segmentation System Using a Genetic Algorithm}, PAGES = {362--369}, } @INPROCEEDINGS{Kargupta1991, CROSSREF = {Belew1991}, AUTHOR = {Hillol Kargupta and R. E. Smith}, TITLE = {System Identification with Evolving Polynomial Networks}, PAGES = {370--376}, } @INPROCEEDINGS{Kelly1991, CROSSREF = {Belew1991}, AUTHOR = {James D. Kelly and Lawrence Davis}, TITLE = {Hybridizing the Genetic Algorithm and the K-Nearest Neighbors Classification Algorithm}, PAGES = {377--383}, } @INPROCEEDINGS{Rogers1991, CROSSREF = {Belew1991}, AUTHOR = {David Rogers}, TITLE = {{G}/{S}{P}{L}{I}{N}{E}{S}: A Hybrid of {F}riedman's Multivariate Adaptive Regression Splines ({M}{A}{R}{S}) Algorithm with {H}olland's Genetic Algorithm}, PAGES = {384--391}, } @INPROCEEDINGS{Souza1991, CROSSREF = {Belew1991}, AUTHOR = {Pedro S. de Souza and Sarosh N. Talukdar}, TITLE = {Genetic Algorithms in Asynchronous Teams}, PAGES = {392--399}, } @INPROCEEDINGS{Bennett1991, CROSSREF = {Belew1991}, AUTHOR = {Kristin Bennett and Michael C. Ferris and Yannis E. Ioannidis}, TITLE = {A Genetic Algorithm for Database Query Optimization}, PAGES = {400--407}, } @INPROCEEDINGS{Bhuyan1991, CROSSREF = {Belew1991}, AUTHOR = {Jay N. Bhuyan and Vijay V. Raghavan and Venkatesh K. Elayavalli}, TITLE = {Genetic Algorithm for Clustering with an Ordered Representation}, PAGES = {408--415}, } @INPROCEEDINGS{Caldwell1991, CROSSREF = {Belew1991}, AUTHOR = {Craig Caldwell and Victor S. Johnston}, TITLE = {Tracking a Criminal Suspect Through ``Face-Space'' with a Genetic Algorithm}, PAGES = {416--421}, } @INPROCEEDINGS{Calloway1991, CROSSREF = {Belew1991}, AUTHOR = {David L. Calloway}, TITLE = {Using a Genetic Algorithm to Design Binary Phase-Only Filters for Pattern Recognition}, PAGES = {422--429}, } @INPROCEEDINGS{Gabbert1991, CROSSREF = {Belew1991}, AUTHOR = {Paula S. Gabbert and Donald E. Brown and Christopher L. Huntley and Bernard P. Markowicz and David E. Sappington}, TITLE = {A System for Learning Routes and Schedules with Genetic Algorithms}, PAGES = {430--436}, } @INPROCEEDINGS{Horner1991, CROSSREF = {Belew1991}, AUTHOR = {Andrew Horner and David E. Goldberg}, TITLE = {Genetic Algorithms and Computer-Assisted Music Composition}, PAGES = {437--441}, } @INPROCEEDINGS{Jones1991, CROSSREF = {Belew1991}, AUTHOR = {Donald R. Jones and Mark A. Beltramo}, TITLE = {Solving Partitioning Problems with Genetic Algorithms}, PAGES = {442--449}, } @INPROCEEDINGS{Karr1991a, CROSSREF = {Belew1991}, AUTHOR = {Charles L. Karr}, TITLE = {Design of an Adaptive Fuzzy Logic Controller Using a Genetic Algorithm}, PAGES = {450--457}, } @INPROCEEDINGS{Kosak1991, CROSSREF = {Belew1991}, AUTHOR = {Corey Kosak and Joe Marks and Stuart Shieber}, TITLE = {A Parallel Genetic Algorithm for Network-Diagram Layout}, PAGES = {458--465}, } @INPROCEEDINGS{Mansour1991, CROSSREF = {Belew1991}, AUTHOR = {Nashat Mansour and Geoffrey C. Fox}, TITLE = {A Hybrid Genetic Algorithm for Task Allocation in Multicomputers}, PAGES = {466--473}, } @INPROCEEDINGS{Nakano1991, CROSSREF = {Belew1991}, AUTHOR = {Ryohei Nakano and Takeshi Yamada}, TITLE = {Conventional Genetic Algorithms for Job Shop Problems}, PAGES = {474--479}, } @INPROCEEDINGS{Nordvik1991, CROSSREF = {Belew1991}, AUTHOR = {Jean-Pierre Nordvik and Jean-Michel Renders}, TITLE = {Genetic Algorithms and Their Potential for Use in Process Control: A Case Study}, PAGES = {480--486}, } @INPROCEEDINGS{Roth1991, CROSSREF = {Belew1991}, AUTHOR = {Gerhard Roth and Martin D. Levine}, TITLE = {A Genetic Algorithm for Primitive Extraction}, PAGES = {487--494}, } @INPROCEEDINGS{Shonkwiler1991, CROSSREF = {Belew1991}, AUTHOR = {R. Shonkwiler and F. Mendivil and A. Deliu}, TITLE = {Genetic Algorithms for the 1-D Fractal Inverse Problem}, PAGES = {495--501}, } @INPROCEEDINGS{Syswerda1991, CROSSREF = {Belew1991}, AUTHOR = {Gilbert Syswerda and Jeff Palmucci}, TITLE = {The Application of Genetic Algorithms to Resource Scheduling}, PAGES = {502--508}, } @INPROCEEDINGS{Thrift1991, CROSSREF = {Belew1991}, AUTHOR = {Philip Thrift}, TITLE = {Fuzzy Logic Synthesis with Genetic Algorithms}, PAGES = {509--513}, } @INPROCEEDINGS{Wyard1991, CROSSREF = {Belew1991}, AUTHOR = {Peter Wyard}, TITLE = {Context Free Grammar Induction Using Genetic Algorithms}, PAGES = {514--519}, } @INPROCEEDINGS{Bersini1991, CROSSREF = {Belew1991}, AUTHOR = {Hugues Bersini and Francisco J. Varela}, TITLE = {The Immune Recruitment Mechanism: A Selective Evolutionary Strategy}, PAGES = {520--526}, } @INPROCEEDINGS{Ray1991, CROSSREF = {Belew1991}, AUTHOR = {Thomas S. Ray}, TITLE = {Is It Alive or Is It {G}{A}?}, PAGES = {527--534}, } @INPROCEEDINGS{Smith1991, CROSSREF = {Belew1991}, AUTHOR = {Joshua R. Smith}, TITLE = {Designing Biomorphs with an Interactive Genetic Algorithm}, PAGES = {535--538}, } @INPROCEEDINGS{Suzuki1991, CROSSREF = {Belew1991}, AUTHOR = {Keiji Suzuki and Yukinori Kakazu}, TITLE = {An Approach to the Analysis of the Basins of the Associative Memory Model Using Genetic Algorithms}, PAGES = {539--546}, } @INPROCEEDINGS{Todd1991, CROSSREF = {Belew1991}, AUTHOR = {Peter M. Todd and Geoffrey F. Miller}, TITLE = {On the Sympatric Origin of Species: Mercurial Mating in the Quicksilver Model}, PAGES = {547--554}, } @INPROCEEDINGS{Torreele1991, CROSSREF = {Belew1991}, AUTHOR = {Jan Torreele}, TITLE = {Temporal Processing with Recurrent Networks: An Evolutionary Approach}, PAGES = {555--561}, } @INPROCEEDINGS{Whitley1991a, CROSSREF = {Belew1991}, AUTHOR = {Darrell Whitley and Stephen Dominic and Rajarshi Das}, TITLE = {Genetic Reinforcement Learning with Multilayer Neural Networks}, PAGES = {562--569}, } @PROCEEDINGS{Biethahn1995, EDITOR = {J\"org Biethahn and Volker Nissen}, BOOKTITLE = {Evolutionary Algorithms in Management Applications}, TITLE = {Evolutionary Algorithms in Management Applications}, YEAR = {1995}, MONTH = {}, VOLUME = {}, NUMBER = {}, SERIES = {}, ORGANISATION = {}, PUBLISHER = {Springer Verlag}, ADDRESS = {Berlin}, NOTE = {}, SIGNATURE = {Extraordinariat Panny, 462E/I.2} } @INPROCEEDINGS{Nissen1995, CROSSREF = {Biethahn1995}, AUTHOR = {Volker Nissen and J\"org Biethahn}, TITLE = {Determining a Good Inventory Policy with a Genetic Algorithm}, PAGES = {240--249}, } @ARTICLE {Davidor1990, AUTHOR = {Yuval Davidor}, TITLE = {Epistasis Variance: Suitability of a Representation to Genetic Algorithms}, JOURNAL = {Complex Systems}, VOLUME = {4}, NUMBER = {4}, YEAR = {1990}, MONTH = {}, PAGES = {369--383}, NOTE = {}, ABSTRACT = {}, } @BOOK {Beunings1993, AUTHOR = {Janine Beunings and Ludwig B\"olkow and Bernd Heydemann and Biruta Kresling and Claus-Peter Lieckfeld and Claus Mattheck and Werner Nachtigall and Josef Reichholf and Bertram J. Schmidt and Veronika Straa{\ss} and Reinhard Witt}, TITLE = {Bionik: Natur als Vorbild}, PUBLISHER = {PRO FUTURA Verlag}, ADDRESS = {M\"unchen}, YEAR = {1993}, VOLUME = {}, SERIES = {WWF Dokumentationen}, EDITION = {}, MONTH = {}, NOTE = {} } @PROCEEDINGS{Davidor1994, EDITOR = {Y. Davidor and H.-P. Schwefel}, BOOKTITLE = {Parallel Problem Solving From Nature -- PPSN III}, TITLE = {Parallel Problem Solving From Nature -- PPSN III}, YEAR = {1994}, MONTH = {}, VOLUME = {866}, NUMBER = {}, SERIES = {Lecture Notes in Computer Science}, ORGANISATION = {}, PUBLISHER = {Springer Verlag}, ADDRESS = {Berlin}, NOTE = {}, SIGNATURE = {WU Janko, 3136/C.1.2} } @INPROCEEDINGS{Whitley1994, CROSSREF = {Davidor1994}, AUTHOR = {D. Whitley and V. S. Gordon and K. Mathias}, TITLE = {Lamarckian Evolution, The {B}aldwin Effect and Function Optimization}, PAGES = {6--15}, } @INPROCEEDINGS{Mattfeld1994, CROSSREF = {Davidor1994}, AUTHOR = {D. C. Mattfeld and H. Kopfer and C. Bierwirth}, TITLE = {Control of Parallel Population Dynamics by Social-Like Behavior of {G}{A}-Individuals}, PAGES = {16--25}, } @INPROCEEDINGS{Chiva1994, CROSSREF = {Davidor1994}, AUTHOR = {E. Chiva and P. Tarroux}, TITLE = {Studying Genotype-Phenotype Interactions: {A} Model of the Evolution of the Cell Regulation Network}, PAGES = {26--35}, } @INPROCEEDINGS{Yoshida1994, CROSSREF = {Davidor1994}, AUTHOR = {Y. Yoshida and N. Adachi}, TITLE = {A Diploid Genetic Algorithm for Preserving Population Diversity -- {P}seudo-Meiosis {G}{A}}, PAGES = {36--45}, } @INPROCEEDINGS{Paredis1994, CROSSREF = {Davidor1994}, AUTHOR = {J. Paredis}, TITLE = {Co-evolutionary Constraint Satisfaction}, PAGES = {46--55}, } @INPROCEEDINGS{Beyer1994, CROSSREF = {Davidor1994}, AUTHOR = {H. G. Beyer}, TITLE = {Towards a Theory of `{E}volution {S}trategies': {R}esults for $(1+,\lambda)$--Strategies on (Nearly) Arbitrary Fitness Functions}, PAGES = {58--67}, } @INPROCEEDINGS{Dzubera1994, CROSSREF = {Davidor1994}, AUTHOR = {J. Dzubera and D. Whitley}, TITLE = {Advanced Correlation Analysis of Operators for the Traveling Salesman Problem}, PAGES = {68--77}, } @INPROCEEDINGS{Eiben1994, CROSSREF = {Davidor1994}, AUTHOR = {A. E. Eiben and P.-E. Rau\'{e} and Zs. Ruttkay}, TITLE = {Genetic Algorithms with Multi-Parent Recombination}, PAGES = {78--87}, } @INPROCEEDINGS{Asoh1994a, CROSSREF = {Davidor1994}, AUTHOR = {H. Asoh and H. M\"uhlenbein}, TITLE = {On the Mean Convergence Time of Evolutionary Algorithms without Selection and Mutation}, PAGES = {88--97}, } @INPROCEEDINGS{Asoh1994b, CROSSREF = {Davidor1994}, AUTHOR = {H. Asoh and H. M\"uhlenbein}, TITLE = {On the Mean Convergence Time of Evolutionary Algorithms without Selection and Mutation}, PAGES = {98--107}, } @INPROCEEDINGS{Bui1994, CROSSREF = {Davidor1994}, AUTHOR = {T. N. Bui and B.-R. Moon}, TITLE = {Analyzing Hyperplane Synthesis in Genetic Algorithms Using Clustered Schemeta}, PAGES = {108--118}, } @INPROCEEDINGS{Thierens1994, CROSSREF = {Davidor1994}, AUTHOR = {D. Thierens and D. Goldberg}, TITLE = {Convergence Models of Genetic Algorithm Selection Schemes}, PAGES = {119--129}, } @INPROCEEDINGS{Nakano1994, CROSSREF = {Davidor1994}, AUTHOR = {R. Nakano and Y. Davidor and T. Yamada}, TITLE = {Optimal Population Size under Constant Computation Cost}, PAGES = {130--138}, } @INPROCEEDINGS{Rudolph1994, CROSSREF = {Davidor1994}, AUTHOR = {G. Rudolph}, TITLE = {An Evolutionary Algorithm for Integer Programming}, PAGES = {139--148}, } @INPROCEEDINGS{Horn1994, CROSSREF = {Davidor1994}, AUTHOR = {J. Horn and D. E. Goldberg and K. Deb}, TITLE = {Long Path Problems}, PAGES = {149--158}, } @INPROCEEDINGS{Hammel1994, CROSSREF = {Davidor1994}, AUTHOR = {U. Hammel and T. B\"ack}, TITLE = {Evolution Strategies on Noisy Functions: How to Improve Convergence Properties}, PAGES = {159--168}, } @INPROCEEDINGS{Pal1994, CROSSREF = {Davidor1994}, AUTHOR = {K. F. Pal}, TITLE = {Selection Schemes with Spatial Isolation for Genetic Optimization}, PAGES = {170--179}, } @INPROCEEDINGS{Tang1994, CROSSREF = {Davidor1994}, AUTHOR = {A. Y.-C. Tang and K.-S. Leung}, TITLE = {A Modified Edge Recombination Operator for the Travelling Salesman Problem}, PAGES = {180--188}, } @INPROCEEDINGS{Ostermeier1994, CROSSREF = {Davidor1994}, AUTHOR = {A. Ostermeier and A. Gawelczyk and N. Hansen}, TITLE = {Step-Size Adaptation Based on Non-Local Use of Selection Information}, PAGES = {189--198}, } @INPROCEEDINGS{Schlierkamp1994, CROSSREF = {Davidor1994}, AUTHOR = {D. Schlierkamp-Voosen and H. M\"uhlenbein}, TITLE = {Strategy Adaptation by Competing Subpopulations}, PAGES = {199--208}, } @INPROCEEDINGS{Sebag1994, CROSSREF = {Davidor1994}, AUTHOR = {M. Sebag and M. Schoenauer}, TITLE = {Controlling Crossover through Inductive Learning}, PAGES = {209--218}, } @INPROCEEDINGS{Lorenz1994, CROSSREF = {Davidor1994}, AUTHOR = {D. H. Lorenz}, TITLE = {Derivative Operators for Preference Predicate Evolution}, PAGES = {219--228}, } @INPROCEEDINGS{White1994a, CROSSREF = {Davidor1994}, AUTHOR = {T. White and F. Oppacher}, TITLE = {Adaptive Crossover Using Automata}, PAGES = {229--238}, } @INPROCEEDINGS{Sakanashi1994, CROSSREF = {Davidor1994}, AUTHOR = {H. Sakanashi and K. Suzuki and Y. Kakazu}, TITLE = {Controlling Dynamics of {G}{A} through Filtered Evaluation Function}, PAGES = {239--248}, } @INPROCEEDINGS{Potter1994, CROSSREF = {Davidor1994}, AUTHOR = {M. A. Potter and K. A. De Jong}, TITLE = {A Cooperative Coevolutionary Approach to Function Optimization}, PAGES = {249--257}, } @INPROCEEDINGS{Carse1994, CROSSREF = {Davidor1994}, AUTHOR = {B. Carse and T. C. Fogarty}, TITLE = {A Fuzzy Classifier System Using the {P}ittsburgh Approach}, PAGES = {260--269}, } @INPROCEEDINGS{Giani1994, CROSSREF = {Davidor1994}, AUTHOR = {A. Giani and F. Baiardi and A. Starita}, TITLE = {{Q}-Learning in Evolutionary Rule-Based Systems}, PAGES = {270--289}, } @INPROCEEDINGS{Hartmann1994, CROSSREF = {Davidor1994}, AUTHOR = {U. Hartmann}, TITLE = {On the Complexity of Learning in Classifier Systems}, PAGES = {280--289}, } @INPROCEEDINGS{Wineberg1994, CROSSREF = {Davidor1994}, AUTHOR = {M. Wineberg and F. Oppacher}, TITLE = {A Representation Scheme to Perform Program Induction in a Canonical Genetic Algorithm}, PAGES = {292--301}, } @INPROCEEDINGS{Iba1994a, CROSSREF = {Davidor1994}, AUTHOR = {H. Iba and H. de Garis and T. Sato}, TITLE = {Genetic Programming with Local Hill-Climbing}, PAGES = {302--311}, } @INPROCEEDINGS{Gathercole1994, CROSSREF = {Davidor1994}, AUTHOR = {C. Gathercole and P. Ross}, TITLE = {Dynamic Training Subset Selection for Supervised Learning in Genetic Programming}, PAGES = {312--321}, } @INPROCEEDINGS{Banzhaf1994, CROSSREF = {Davidor1994}, AUTHOR = {W. Banzhaf}, TITLE = {Genotype--Phenotype--Mapping and Neutral Variation -- A Case Study in Genetic Programming}, PAGES = {322--332}, } @INPROCEEDINGS{Jacob1994, CROSSREF = {Davidor1994}, AUTHOR = {C. Jacob}, TITLE = {Genetic L-System Programming}, PAGES = {334--343}, } @INPROCEEDINGS{Das1994, CROSSREF = {Davidor1994}, AUTHOR = {R. Das and M. Mitchell and J. P. Crutchfield}, TITLE = {A Genetic Algorithm Discovers Particle--Based Computation in Cellular Automata}, PAGES = {344--353}, } @INPROCEEDINGS{Oliveira1994, CROSSREF = {Davidor1994}, AUTHOR = {P. P.B.de Oliveira}, TITLE = {Simulation of Exaptive Behavior}, PAGES = {354--364}, } @INPROCEEDINGS{Inayoshi1994a, CROSSREF = {Davidor1994}, AUTHOR = {H. Inayoshi}, TITLE = {Artificial Spacing Patterns in a Network of Interacting Celloids}, PAGES = {365--374}, } @INPROCEEDINGS{Muruzabal1994, CROSSREF = {Davidor1994}, AUTHOR = {J. Muruzabal and A. Munoz}, TITLE = {Diffuse Pattern Learning with Fuzzy {A}{R}{T}{M}{A}{P} and {P}{A}{S}{S}}, PAGES = {376--385}, } @INPROCEEDINGS{Heistermann1994, CROSSREF = {Davidor1994}, AUTHOR = {J. Heistermann}, TITLE = {Different Learning Algorithms for Neural Networks -- A Comparative Study}, PAGES = {386--396}, } @INPROCEEDINGS{Reilly1994, CROSSREF = {Davidor1994}, AUTHOR = {U.-M. O'Reilly and F. Oppacher}, TITLE = {Program Search with a Hierarchical Variable Length Representation: Genetic Programming, Simulated Annealing and Hill Climbing}, PAGES = {397--406}, } @INPROCEEDINGS{Laursen1994, CROSSREF = {Davidor1994}, AUTHOR = {P. S. Laursen}, TITLE = {Problem Independent Parallel Simulated Annealing Using Selection and Migration}, PAGES = {408--417}, } @INPROCEEDINGS{Baeck1994, CROSSREF = {Davidor1994}, AUTHOR = {T. B\"ack}, TITLE = {Parallel Optimization of Evolutionary Algorithms}, PAGES = {418--427}, } @INPROCEEDINGS{Chen1994, CROSSREF = {Davidor1994}, AUTHOR = {H. Chen and N. S. Flann}, TITLE = {Parallel Simulated Annealing and Genetic Algorithms: A Space of Hybrid Methods}, PAGES = {428--438}, } @INPROCEEDINGS{Braun1994, CROSSREF = {Davidor1994}, AUTHOR = {H. Braun and P. Zagorski}, TITLE = {{E}{N}{Z}{O}-{M} -- A Hybrid Approach for Optimizing Neural Networks by Evolution and Learning}, PAGES = {440--451}, } @INPROCEEDINGS{Ronald1994, CROSSREF = {Davidor1994}, AUTHOR = {E. Ronald and M. Schoenauer}, TITLE = {Genetic Lander: An Experiment in Accurate Neuro-Genetic Control}, PAGES = {452--461}, } @INPROCEEDINGS{Zhang1994, CROSSREF = {Davidor1994}, AUTHOR = {B.-T. Zhang}, TITLE = {Effects of {O}ccam's Razor in Evolving Sigma-Pi Neural Nets}, PAGES = {462--471}, } @INPROCEEDINGS{Born1994, CROSSREF = {Davidor1994}, AUTHOR = {J. Born and I. Santibanez-Koref and H.-M. Voigt}, TITLE = {Designing Neural Networks by Adaptively Building Blocks in Cascades}, PAGES = {472--481}, } @INPROCEEDINGS{Pipe1994, CROSSREF = {Davidor1994}, AUTHOR = {A. G. Pipe and T. C. Fogarty and A. Winfield}, TITLE = {Hybrid Adaptive Heuristic Critic Architectures for Learning in Mazes with Continuous Search Spaces}, PAGES = {482--491}, } @INPROCEEDINGS{Utecht1994, CROSSREF = {Davidor1994}, AUTHOR = {U. Utecht and K. Trint}, TITLE = {Mutation Operators for Structure Evolution of Neural Networks}, PAGES = {492--501}, } @INPROCEEDINGS{Hauser1994, CROSSREF = {Davidor1994}, AUTHOR = {R. Hauser and R. M\"anner}, TITLE = {Implementation of Standard Genetic Algorithms on {M}{I}{M}{D} Machines}, PAGES = {504--513}, } @INPROCEEDINGS{Seredynski1994, CROSSREF = {Davidor1994}, AUTHOR = {F. Seredynski}, TITLE = {Loosely Coupled Distributed Genetic Algorithms}, PAGES = {514--523}, } @INPROCEEDINGS{Higuchi1994, CROSSREF = {Davidor1994}, AUTHOR = {T. Higuchi and H. Iba and B. Manderick}, TITLE = {Applying Evolvable Hardware to Autonomous Agents}, PAGES = {524--533}, } @INPROCEEDINGS{Marin1994, CROSSREF = {Davidor1994}, AUTHOR = {F. J. Marin and O. Trelles-Salazar and F. Sandoval}, TITLE = {Genetic Algorithms on the {L}{A}{N}-Message Passing Architectures Using {P}{V}{M}: Application to the Routing Problem}, PAGES = {534--543}, } @INPROCEEDINGS{Hill1994, CROSSREF = {Davidor1994}, AUTHOR = {A. M. Hill and S.-M. Kang}, TITLE = {Genetic Algorithm Based Design Optimization of {C}{M}{O}{S} {V}{L}{S}{I} Circuits}, PAGES = {546--555}, } @INPROCEEDINGS{Ross1994, CROSSREF = {Davidor1994}, AUTHOR = {P. Ross and D. Corne and H.-L. Fang}, TITLE = {Improving Evolutionary Timetabling with Delta Evaluation and Directed Mutation}, PAGES = {556--565}, } @INPROCEEDINGS{VanWezel1994, CROSSREF = {Davidor1994}, AUTHOR = {M. C. VanWezel and J. N. Kok and J. VanDenBerg and W. VanKampen}, TITLE = {Genetic Improvement of Railway Timetables}, PAGES = {566--575}, } @INPROCEEDINGS{Cobb1994, CROSSREF = {Davidor1994}, AUTHOR = {H. G. Cobb and P. Bock}, TITLE = {Using a Genetic Algorithm to Search for the Representational Bias of a Collective Reinforcement Learner}, PAGES = {576--587}, } @INPROCEEDINGS{Lienig1994, CROSSREF = {Davidor1994}, AUTHOR = {J. Lienig and H. Brandt}, TITLE = {An Evolutionary Algorithm for the Routing of Multi-Chip Modules}, PAGES = {588--597}, } @INPROCEEDINGS{Pullen1994, CROSSREF = {Davidor1994}, AUTHOR = {S. P. Pullen and B. W. Parkinson}, TITLE = {System Design under Uncertainty: Evolutionary Optimization of the Gravity Probe-B Spacecraft}, PAGES = {598--607}, } @INPROCEEDINGS{Karcz1994, CROSSREF = {Davidor1994}, AUTHOR = {I. Karcz-Duleba}, TITLE = {Soft Selection in {D}-optimal Designs}, PAGES = {608--616}, } @INPROCEEDINGS{Inayoshi1994b, CROSSREF = {Davidor1994}, AUTHOR = {H. Inayoshi and B. Manderick}, TITLE = {The Weighted Graph Bi-Partitioning Problem: A Look at {G}{A} Performance}, PAGES = {617--625}, } @INPROCEEDINGS{Surry1994, CROSSREF = {Davidor1994}, AUTHOR = {P. Surry and N. J. Radcliffe}, TITLE = {{R}{P}{L}2: A Language and Parallel Framework for Evolutionary Computing}, PAGES = {628--637}, } @PROCEEDINGS{Davis1987a, EDITOR = {Lawrence Davis}, BOOKTITLE = {Genetic Algorithms and Simulated Annealing}, TITLE = {Genetic Algorithms and Simulated Annealing}, YEAR = {1987}, MONTH = {}, VOLUME = {}, NUMBER = {}, SERIES = {Research Notes in Artificial Intelligence}, ORGANISATION = {BBN Laboratories}, PUBLISHER = {Pitman Publishing}, ADDRESS = {London}, NOTE = {}, SIGNATURE = {WU, Janko, 788/J.3} } @INPROCEEDINGS{Davis1987b, CROSSREF = {Davis1987a}, AUTHOR = {Lawrence Davis and Martha Steenstrup}, TITLE = {Genetic Algorithms and Simulated Annealing: An Overview}, PAGES = {1--11}, } @INPROCEEDINGS{Glover1987, CROSSREF = {Davis1987a}, AUTHOR = {David E. Glover}, TITLE = {Solving a Complex Keyboard Configuration Problem Through Generalized Adaptive Search}, PAGES = {12--31}, } @INPROCEEDINGS{Axelrod1987, CROSSREF = {Davis1987a}, AUTHOR = {Robert Axelrod}, TITLE = {The Evolution of Strategies in the Iterated Prisoner's Dilemma}, PAGES = {32--41}, } @INPROCEEDINGS{Grefenstette1987b, CROSSREF = {Davis1987a}, AUTHOR = {John J. Grefenstette}, TITLE = {Incorporating Problem Specific Knowledge into Genetic Algorithms}, PAGES = {42--60}, } @INPROCEEDINGS{Booker1987, CROSSREF = {Davis1987a}, AUTHOR = {Lashon Booker}, TITLE = {Improving Search in Genetic Algorithms}, PAGES = {61--73}, } @INPROCEEDINGS{Goldberg1987d, CROSSREF = {Davis1987a}, AUTHOR = {David E. Goldberg}, TITLE = {Simple Genetic Algorithms and the Minimal, Deceptive Problem}, PAGES = {74--88}, } @INPROCEEDINGS{Schaffer1987a, CROSSREF = {Davis1987a}, AUTHOR = {J. David Schaffer}, TITLE = {Some Effects of Selection Procedures on Hyperplane Sampling}, PAGES = {89--103}, } @INPROCEEDINGS{Wilson1987a, CROSSREF = {Davis1987a}, AUTHOR = {Stewart W. Wilson}, TITLE = {Hierarchical Credit Allocation in a Classifier System}, PAGES = {104--115}, } @INPROCEEDINGS{Holland1987a, CROSSREF = {Davis1987a}, AUTHOR = {John H. Holland and Keith J. Holyoak and Richard E. Nisbett and Paul R. Thagard}, TITLE = {Classifier Systems, Q-Morphisms, and Induction}, PAGES = {116--128}, } @INPROCEEDINGS{Robertson1987a, CROSSREF = {Davis1987a}, AUTHOR = {George Robertson}, TITLE = {Parallel Implementation of Genetic Algorithms in a Classifier System}, PAGES = {129--140}, } @INPROCEEDINGS{Selman1987, CROSSREF = {Davis1987a}, AUTHOR = {Bart Selman and Gaeme Hirst}, TITLE = {Parsing as an Energy Minimization Problem}, PAGES = {141--154}, } @INPROCEEDINGS{Touretzky1987, CROSSREF = {Davis1987a}, AUTHOR = {Davis S. Touretzky and Geoffrey E. Hinton}, TITLE = {Pattern Matching and Variable Binding in Stochastic Neural Network}, PAGES = {155--169}, } @INPROCEEDINGS{Ackley1987a, CROSSREF = {Davis1987a}, AUTHOR = {David H. Ackley}, TITLE = {An Empirical Study of Bit Vector Function Optimization}, PAGES = {170--204}, } @PROCEEDINGS{Davis1991b, EDITOR = {Lawrence Davis}, BOOKTITLE = {Handbook of Genetic Algorithms}, TITLE = {Handbook of Genetic Algorithms}, YEAR = {1991}, MONTH = {}, VOLUME = {}, NUMBER = {}, SERIES = {}, ORGANISATION = {University of California, San Diego}, PUBLISHER = {Van Nostrand Reinhold}, ADDRESS = {New York}, NOTE = {}, SIGNATURE = {WU, Janko, 2348/G.2.1} } @INPROCEEDINGS{Davis1991c, CROSSREF = {Davis1991b}, AUTHOR = {Lawrence Davis}, TITLE = {A Genetic Algorithms Tutorial}, PAGES = {1--101}, } @INPROCEEDINGS{Bramlette1991b, CROSSREF = {Davis1991b}, AUTHOR = {Mark F. Bramlette and Eugene E. Bouchard}, TITLE = {Genetic Algorithms in Parametric Design of Aircraft}, PAGES = {109--123}, } @INPROCEEDINGS{Cox1991, CROSSREF = {Davis1991b}, AUTHOR = {Louis Anthony Cox Jr. and Lawrence Davis and Yuping Qiu}, TITLE = {Dynamic Anticipatory Routing in Circuit-Switched Telecommunications Networks}, PAGES = {124--143}, } @INPROCEEDINGS{Davidor1991a, CROSSREF = {Davis1991b}, AUTHOR = {Yuval Davidor}, TITLE = {A Genetic Algorithm Applied to Robot Trajectory Generation}, PAGES = {144--165}, } @INPROCEEDINGS{Forrest1991a, CROSSREF = {Davis1991b}, AUTHOR = {Stephanie Forrest and Gottfried Mayer-Kress}, TITLE = {Genetic Algorithms, Nonlinear Dynamical Systems, and Models of International Security}, PAGES = {166--185}, } @INPROCEEDINGS{Grefenstette1991b, CROSSREF = {Davis1991b}, AUTHOR = {John J. Grefenstette}, TITLE = {Strategy Acquisition with Genetic Algorithms}, PAGES = {186--201}, } @INPROCEEDINGS{Harp1991, CROSSREF = {Davis1991b}, AUTHOR = {Steven A. Harp and Tariq Samad}, TITLE = {Genetic Synthesis of Neural Network Architecture}, PAGES = {202--221}, } @INPROCEEDINGS{Karr1991b, CROSSREF = {Davis1991b}, AUTHOR = {Charles L. Karr}, TITLE = {Air-Injected Hydrocyclone Optimization via Genetic Algorithm}, PAGES = {222--236}, } @INPROCEEDINGS{Liepins1991b, CROSSREF = {Davis1991b}, AUTHOR = {Gunar E. Liepins and W. D. Potter}, TITLE = {A Genetic Algorithm to Multiple-Fault Diagnosis}, PAGES = {237--250}, } @INPROCEEDINGS{Lucasius1991, CROSSREF = {Davis1991b}, AUTHOR = {C. B. Lucasius and M. J. J. Blommers and L. M. C. Buydens and G. Kateman}, TITLE = {A Genetic Algorithm for Confirmational Analysis of DNA}, PAGES = {251--281}, } @INPROCEEDINGS{Montana1991, CROSSREF = {Davis1991b}, AUTHOR = {David J. Montana}, TITLE = {Automated Parameter Tuning for Interpretation of Synthetic Images}, PAGES = {282--311}, } @INPROCEEDINGS{Powell1991, CROSSREF = {Davis1991b}, AUTHOR = {David J. Powell and Michael M. Skolnick and Siu Shing Tong}, TITLE = {Interdigitation: A Hybrid Technique for Engineering Design Optimization Employing Genetic Algorithms, Expert Systems, and Numerical Optimization}, PAGES = {312--331}, } @INPROCEEDINGS{Syswerda1991b, CROSSREF = {Davis1991b}, AUTHOR = {Gilbert Syswerda}, TITLE = {Schedule Optimization Using Genetic Algorithms}, PAGES = {332--349}, } @INPROCEEDINGS{Whitley1991b, CROSSREF = {Davis1991b}, AUTHOR = {Darrell Whitley and Timothy Starkweather and Daniel Shaner}, TITLE = {The Traveling Salesman and Sequence Scheduling: Quality Solutions Using Genetic Edge Recombination}, PAGES = {350--372}, } @INPROCEEDINGS{Davis1991d, CROSSREF = {Davis1991b}, AUTHOR = {Lawrence Davis and John J. Grefenstette}, TITLE = {Concerning {G}{E}{N}{E}{S}{I}{S} and {O}{O}{G}{A}}, PAGES = {374--377}, } @ARTICLE {DeJong1980, AUTHOR = {Kenneth A. DeJong}, TITLE = {Adaptive System Design: A Genetic Approach}, JOURNAL = {IEEE Transactions on Systems, Man, and Cybernetics}, VOLUME = {SMC 10}, NUMBER = {9}, YEAR = {1980}, MONTH = {September}, PAGES = {566--574}, NOTE = {}, ABSTRACT = {}, } @PROCEEDINGS{Farmer1986, EDITOR = {Doyne Farmer and Alan Lapedes and Norman Packard and Burton Wendroff}, BOOKTITLE = {Evolution, Games and Learning: Models for Adaptation in Machines and Nature -- Proceedings of the Fifth Annual International Conference of the Center for Nonlinear Studies}, TITLE = {Evolution, Games and Learning: Models for Adaptation in Machines and Nature}, YEAR = {1986}, MONTH = {}, VOLUME = {}, NUMBER = {}, SERIES = {}, ORGANISATION = {Los Alamos National Laboratory}, PUBLISHER = {North-Holland}, ADDRESS = {Amsterdam}, NOTE = {Reprinted from Physica D, Vol. 22D(1986), Nos. 1--3}, SIGNATURE = {WU, Janko, 773/K.3} } @INPROCEEDINGS{Farmer1986a, CROSSREF = {Farmer1986}, AUTHOR = {J. Doyne Farmer and Norman H. Packard}, TITLE = {Evolution, Games, and Learning: Models for Adaptation in Machines and Nature. An Introduction to the Proceedings of the CNLS Conference, {L}os {A}lamos, {M}ay 1985}, PAGES = {vii--xii}, } @INPROCEEDINGS{Rota1986, CROSSREF = {Farmer1986}, AUTHOR = {G. C. Rota}, TITLE = {In Memoriam of {S}tan {U}lam -- The Barrier of Meaning}, PAGES = {1--3}, } @INPROCEEDINGS{Ulam1986, CROSSREF = {Farmer1986}, AUTHOR = {Stan Ulam and R. Schrandt}, TITLE = {Some Elementary Attempts at Numerical Modeling of Problems Concerning Rates of Evolutionary Processes}, PAGES = {4--12}, } @INPROCEEDINGS{Good1986, CROSSREF = {Farmer1986}, AUTHOR = {I. J. Good}, TITLE = {(Neo)''-{D}arwinism}, PAGES = {13--30}, } @INPROCEEDINGS{Valentine1986, CROSSREF = {Farmer1986}, AUTHOR = {J. W. Valentine and T. D. 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Brynn Hibbert}, TITLE = {Display of Chemical Structures in Two Dimensions and the Evolution of Molecular Recognition}, PAGES = {637}, } @INPROCEEDINGS{Iwamoto1993, CROSSREF = {Forrest1993}, AUTHOR = {Takashi Iwamoto and Wolfgang Banzhaf and Kazuo Kyuma}, TITLE = {Topological Aspects of Genetic Algorithms}, PAGES = {638}, } @INPROCEEDINGS{Juliany1993, CROSSREF = {Forrest1993}, AUTHOR = {Jenny Juliany and Michael D. Vose}, TITLE = {The Genetic Algorithm Fractal}, PAGES = {639}, } @INPROCEEDINGS{Kargupta1993, CROSSREF = {Forrest1993}, AUTHOR = {Hillol Kargupta}, TITLE = {Information Transmission in Genetic Algorithms and Shannon's Second Theorem}, PAGES = {640}, } @INPROCEEDINGS{Kido1993, CROSSREF = {Forrest1993}, AUTHOR = {Takashi Kido and Hiroaki Kitano and Masakuzo Nakanishi}, TITLE = {A Hybrid Search for Genetic Algorithms: Combining Genetic Algorithms, {T}{A}{B}{U} Search, and Simulated Annealing}, PAGES = {641}, } @INPROCEEDINGS{Lopez1993, CROSSREF = {Forrest1993}, AUTHOR = {Luis Lopez}, TITLE = {Inverse Relationship Between Complexity and Probability of Full Deception in Trap Functions}, PAGES = {642}, } @INPROCEEDINGS{Mahfoud1993, CROSSREF = {Forrest1993}, AUTHOR = {Samir W. Mahfoud}, TITLE = {Simple Analytical Models of Genetic Algorithms for Multimodal Function Optimization}, PAGES = {643}, } @INPROCEEDINGS{Maniezzo1993a, CROSSREF = {Forrest1993}, AUTHOR = {Vittorio Maniezzo}, TITLE = {Granularity Evolution}, PAGES = {644}, } @INPROCEEDINGS{Markus1993, CROSSREF = {Forrest1993}, AUTHOR = {Andr\'{a}s M\'{a}rkus}, TITLE = {Dual Insights into Genetic Algorithms}, PAGES = {645}, } @INPROCEEDINGS{Mayer1993, CROSSREF = {Forrest1993}, AUTHOR = {Matthias Mayer and Fikret Ercal}, TITLE = {Genetic Algorithms for Vertex Splitting in {D}{A}{G}s}, PAGES = {646}, } @INPROCEEDINGS{Mitchell1993a, CROSSREF = {Forrest1993}, AUTHOR = {Melanie Mitchell and John H. Holland}, TITLE = {When Will a Genetic Algorithm Outperform Hill Climbing?}, PAGES = {647}, } @INPROCEEDINGS{Muehlenbein1993, CROSSREF = {Forrest1993}, AUTHOR = {Heinz M\"uhlenbein and Dirk Schlierkamp-Voosen}, TITLE = {Optimal Interaction of Mutation and Crossover in the Breeder Genetic Algorithm}, PAGES = {648}, } @INPROCEEDINGS{Munemoto1993, CROSSREF = {Forrest1993}, AUTHOR = {Masaharu Munemoto and Yoshiaki Takai and Yoshiharu Sato}, TITLE = {An Efficient Migration Scheme for Subpopulation-Based Asynchronously Parallel Genetic Algorithms}, PAGES = {649}, } @INPROCEEDINGS{Orvosh1993, CROSSREF = {Forrest1993}, AUTHOR = {David Orvosh and Lawrence Davis}, TITLE = {Shall We Repair? Genetic Algorithms, Combinatorial Optimization, and Feasibility Constraints}, PAGES = {650}, } @INPROCEEDINGS{Park1993, CROSSREF = {Forrest1993}, AUTHOR = {Kihong Park}, TITLE = {A Lower-Bound Result on the Power of Genetic Algorithms}, PAGES = {651}, } @INPROCEEDINGS{Sen1993, CROSSREF = {Forrest1993}, AUTHOR = {Sandip Sen}, TITLE = {Improving Classification Accuracy through Performance History}, PAGES = {652}, } @INPROCEEDINGS{Smith1993a, CROSSREF = {Forrest1993}, AUTHOR = {Robert E. Smith}, TITLE = {Adaptively Resizing Populations: An Algorithm and Analysis}, PAGES = {653}, } @INPROCEEDINGS{Spencer1993, CROSSREF = {Forrest1993}, AUTHOR = {Graham F. Spencer}, TITLE = {Automatic Generation of Programs for Crawling and Walking}, PAGES = {654}, } @INPROCEEDINGS{Sun1993, CROSSREF = {Forrest1993}, AUTHOR = {Chuen-Tsai Sun and Jyh-Shing Jang}, TITLE = {Using Genetic Algorithms in Structuring a Fuzzy Rulebase}, PAGES = {655}, } @INPROCEEDINGS{Tanaka1993, CROSSREF = {Forrest1993}, AUTHOR = {Yoshiaki Tanaka and Akio Ishiguro and Yoshiki Uchikawa}, TITLE = {A Genetic Algorithms' Application to Inverse Problems in Electromagnetics}, PAGES = {656}, } @INPROCEEDINGS{Voigt1993, CROSSREF = {Forrest1993}, AUTHOR = {Hans Michael Voigt and Joachim Born and Ivan Santibanez-Koref}, TITLE = {Multivalued Evolutionary Algorithms}, PAGES = {657}, } @INPROCEEDINGS{Whitley1993a, CROSSREF = {Forrest1993}, AUTHOR = {Darrell Whitley}, TITLE = {Cellular Genetic Algorithms}, PAGES = {658}, } @INPROCEEDINGS{Yanagiya1993, CROSSREF = {Forrest1993}, AUTHOR = {Masayuki Yanagiya}, TITLE = {A Simple Mutation-Dependent Genetic Algorithm}, PAGES = {659}, } @INPROCEEDINGS{Zeigler1993, CROSSREF = {Forrest1993}, AUTHOR = {Bernard P. Zeigler and Jinwoo Kim}, TITLE = {Asynchronous Genetic Algorithms on Parallel Computers}, PAGES = {660}, } @BOOK {Goldberg1989, AUTHOR = {David E. Goldberg}, TITLE = {Genetic Algorithms in Search, Optimization \& Machine Learning}, PUBLISHER = {Addison-Wesley}, ADDRESS = {Reading, MA}, YEAR = {1989}, VOLUME = {}, SERIES = {}, EDITION = {}, MONTH = {}, NOTE = {} } @ARTICLE {Goldberg1989d, AUTHOR = {David E. Goldberg}, TITLE = {Genetic Algorithms and {W}alsh Functions: Part {I}, A Gentle Introduction}, JOURNAL = {Complex Systems}, VOLUME = {3}, NUMBER = {2}, YEAR = {1989}, MONTH = {}, PAGES = {129--152}, NOTE = {}, ABSTRACT = {}, } @ARTICLE {Goldberg1989e, AUTHOR = {David E. Goldberg}, TITLE = {Genetic Algorithms and {W}alsh Functions: Part {I}{I}, Deception and its Analysis}, JOURNAL = {Complex Systems}, VOLUME = {3}, NUMBER = {2}, YEAR = {1989}, MONTH = {}, PAGES = {153--171}, NOTE = {}, ABSTRACT = {}, } @ARTICLE {Goldberg1989c, AUTHOR = {David E. Goldberg and Bradley Korb and Kalyanmoy Deb}, TITLE = {Messy Genetic Algorithms: Motivation, Analysis, and First Results}, JOURNAL = {Complex Systems}, VOLUME = {3}, NUMBER = {5}, YEAR = {1990}, MONTH = {}, PAGES = {493--530}, NOTE = {}, ABSTRACT = {}, } @ARTICLE {Goldberg1990, AUTHOR = {D. E. Goldberg and C. L. Bridges}, TITLE = {An Analysis of a Reordering Operator on a GA-Hard Problem}, JOURNAL = {Biological Cybernetics}, VOLUME = {62}, NUMBER = {5}, YEAR = {1990}, MONTH = {}, PAGES = {397--405}, NOTE = {}, ABSTRACT = {}, } @ARTICLE {Goldberg1990a, AUTHOR = {David E. Goldberg and Kalyanmoy Deb and Bradley Korb}, TITLE = {Messy Genetic Algorithms Revisited: Studies in Mixed Size and Scale}, JOURNAL = {Complex Systems}, VOLUME = {4}, NUMBER = {4}, YEAR = {1990}, MONTH = {}, PAGES = {415--444}, NOTE = {}, ABSTRACT = {}, } @ARTICLE {Goldberg1990b, AUTHOR = {David E. Goldberg}, TITLE = {A Note on {B}oltzmann Tournament Selection for Genetic Algorithms and Population--Oriented Simulated Annealing}, JOURNAL = {Complex Systems}, VOLUME = {4}, NUMBER = {4}, YEAR = {1990}, MONTH = {}, PAGES = {445--460}, NOTE = {}, ABSTRACT = {}, } @ARTICLE {Goldberg1994, AUTHOR = {David E. Goldberg}, TITLE = {Genetic and Evolutionary Algorithms Come of Age}, JOURNAL = {Communications of the ACM}, VOLUME = {37}, NUMBER = {3}, YEAR = {1994}, MONTH = {March}, PAGES = {113--119}, NOTE = {}, ABSTRACT = {}, } @PROCEEDINGS{Grefenstette1985, EDITOR = {John J. Grefenstette}, BOOKTITLE = {Proceedings of the First International Conference on Genetic Algorithms and their Applications}, TITLE = {Proceedings of the First International Conference on Genetic Algorithms and their Applications (ICGA'85)}, YEAR = {1985}, MONTH = {}, VOLUME = {}, NUMBER = {}, SERIES = {}, ORGANISATION = {Carnegie-Mellon University}, PUBLISHER = {Lawrence Erlbaum Associates}, ADDRESS = {Hillsdale, New Jersey}, NOTE = {} } @INPROCEEDINGS{Holland1985, CROSSREF = {Grefenstette1985}, AUTHOR = {John H. Holland}, TITLE = {Properties of the Bucket Brigade}, PAGES = {1--7}, } @INPROCEEDINGS{Goldberg1985a, CROSSREF = {Grefenstette1985}, AUTHOR = {David E. Goldberg}, TITLE = {Genetic Algorithms and Rules Learning in Dynamic Systems Control}, PAGES = {8--15}, } @INPROCEEDINGS{Wilson1985a, CROSSREF = {Grefenstette1985}, AUTHOR = {Stewart W. Wilson}, TITLE = {Knowledge Growth in an Artificial Animal}, PAGES = {16--23}, } @INPROCEEDINGS{Forrest1985, CROSSREF = {Grefenstette1985}, AUTHOR = {Stephanie Forrest}, TITLE = {Implementing Semantic Network Structures Using the Classifier System}, PAGES = {24--44}, } @INPROCEEDINGS{Westerdale1985, CROSSREF = {Grefenstette1985}, AUTHOR = {Thomas H. Westerdale}, TITLE = {The Bucket Brigade is not Genetic}, PAGES = {45--59}, } @INPROCEEDINGS{Rendell1985, CROSSREF = {Grefenstette1985}, AUTHOR = {Larry A. Rendell}, TITLE = {Genetic Plans and the Probabilistic Learning System: Synthesis and Results}, PAGES = {60--73}, } @INPROCEEDINGS{Schaffer1985a, CROSSREF = {Grefenstette1985}, AUTHOR = {J. David Schaffer}, TITLE = {Learning Multiclass Pattern Discrimination}, PAGES = {74--79}, } @INPROCEEDINGS{Booker1985, CROSSREF = {Grefenstette1985}, AUTHOR = {Lashon B. Booker}, TITLE = {Improving the Performance of Genetic Algorithms in Classifier Systems}, PAGES = {80--92}, } @INPROCEEDINGS{Schaffer1985b, CROSSREF = {Grefenstette1985}, AUTHOR = {J. David Schaffer}, TITLE = {Multiple Objective Optimization with Vector Evaluated Genetic Algorithms}, PAGES = {93--100}, } @INPROCEEDINGS{Baker1985, CROSSREF = {Grefenstette1985}, AUTHOR = {James E. Baker}, TITLE = {Adaptive Selection Methods for Genetic Algorithms}, PAGES = {101--111}, } @INPROCEEDINGS{Grefenstette1985a, CROSSREF = {Grefenstette1985}, AUTHOR = {John J. Grefenstette and J. Michael Fitzpatrick}, TITLE = {Genetic Search with Approximate Function Evaluation}, PAGES = {112--120}, } @INPROCEEDINGS{Ackley1985, CROSSREF = {Grefenstette1985}, AUTHOR = {David H. Ackley}, TITLE = {A Connectionist Algorithm for Genetic Search}, PAGES = {121--135}, } @INPROCEEDINGS{Davis1985, CROSSREF = {Grefenstette1985}, AUTHOR = {Lawrence Davis}, TITLE = {Job Scheduling with Genetic Algorithms}, PAGES = {136--140}, } @INPROCEEDINGS{Fourman1985, CROSSREF = {Grefenstette1985}, AUTHOR = {Michael P. Fourman}, TITLE = {Compaction of Symbolic Layout Using Genetic Algorithms}, PAGES = {141--153}, } @INPROCEEDINGS{Goldberg1985b, CROSSREF = {Grefenstette1985}, AUTHOR = {David E. Goldberg and Robert Lingle}, TITLE = {Alleles, Loci, and the Traveling Saleman Problem}, PAGES = {154--159}, } @INPROCEEDINGS{Grefenstette1985b, CROSSREF = {Grefenstette1985}, AUTHOR = {John J. Grefenstette and Rajeev Gopal and Brian J. Rosmaita and Dirk Van Gucht}, TITLE = {Genetic Algorithms for the Traveling Salesman Problem}, PAGES = {160--168}, } @INPROCEEDINGS{Jong1985, CROSSREF = {Grefenstette1985}, AUTHOR = {Kenneth A. DeJong}, TITLE = {Genetic Algorithms: A 10 Year Perspective}, PAGES = {169--177}, } @INPROCEEDINGS{Zhou1985, CROSSREF = {Grefenstette1985}, AUTHOR = {Hayong Zhou}, TITLE = {Classifier Systems with Long Term Memory}, PAGES = {178--182}, } @INPROCEEDINGS{Cramer1985, CROSSREF = {Grefenstette1985}, AUTHOR = {Nichael Lynn Cramer}, TITLE = {A Representation for the Adaptive Generation of Simple Sequential Programs}, PAGES = {183--187}, } @INPROCEEDINGS{Wilson1985b, CROSSREF = {Grefenstette1985}, AUTHOR = {Stewart W. Wilson}, TITLE = {Adaptive `Cortical' Pattern Recognition}, PAGES = {188--196}, } @INPROCEEDINGS{Englander1985, CROSSREF = {Grefenstette1985}, AUTHOR = {Arnold C. Englander}, TITLE = {Machine Learning of Visual Recognition Using Genetic Algorithms}, PAGES = {197--201}, } @INPROCEEDINGS{Smith1985, CROSSREF = {Grefenstette1985}, AUTHOR = {Derek Smith}, TITLE = {Bin Packing with Adaptive Search}, PAGES = {202--207}, } @INPROCEEDINGS{Shaefer1985, CROSSREF = {Grefenstette1985}, AUTHOR = {Craig G. Shaefer}, TITLE = {Directed Trees Method for Fitting a Potential Function}, PAGES = {208--226}, } @ARTICLE {Grefenstette1986, AUTHOR = {John J. Grefenstette}, TITLE = {Optimization of Control Parameters for Genetic Algorithms}, JOURNAL = {IEEE Transactions on Systems, Man, and Cybernetics}, VOLUME = {SMC-16}, NUMBER = {1}, YEAR = {1986}, MONTH = {January/February}, PAGES = {122--128}, NOTE = {}, ABSTRACT = {}, } @PROCEEDINGS{Grefenstette1987, EDITOR = {John J. Grefenstette}, BOOKTITLE = {Proceedings of the Second International Conference on Genetic Algorithms}, TITLE = {Genetic Algorithms and their Applications (ICGA'87)}, YEAR = {1987}, MONTH = {}, VOLUME = {}, NUMBER = {}, SERIES = {}, ORGANISATION = {Massachusetts Instute of Technology}, PUBLISHER = {Lawrence Erlbaum Associates}, ADDRESS = {Hillsdale, New Jersey}, NOTE = {} } @INPROCEEDINGS{Goldberg1987a, CROSSREF = {Grefenstette1987}, AUTHOR = {David E. Goldberg and Philip Segrest}, TITLE = {Finite Markov Chain Analysis of Genetic Algorithms}, PAGES = {1--8}, } @INPROCEEDINGS{Bridges1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Clayton L. Bridges and David E. Goldberg}, TITLE = {An Analysis of Reproduction and Crossover in a Binary-Coded Genetic Algorithm}, PAGES = {9--13}, } @INPROCEEDINGS{Baker1987, CROSSREF = {Grefenstette1987}, AUTHOR = {James E. Baker}, TITLE = {Reducing Bias and Inefficiency in the Selection Algorithm}, PAGES = {14--21}, } @INPROCEEDINGS{Westerdale1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Thomas H. Westerdale}, TITLE = {Altruism in the Bucket Brigade}, PAGES = {22--26}, } @INPROCEEDINGS{Stadnyk1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Irene Stadnyk}, TITLE = {Schema Recombination in Pattern Recognition Problems}, PAGES = {27--35}, } @INPROCEEDINGS{Schaffer1987, CROSSREF = {Grefenstette1987}, AUTHOR = {J. David Schaffer and Amy Morishima}, TITLE = {An Adaptive Crossover Distribution Mechanism for Genetic Algorithms}, PAGES = {36--40}, } @INPROCEEDINGS{Goldberg1987b, CROSSREF = {Grefenstette1987}, AUTHOR = {David E. Goldberg and Jon Richardson}, TITLE = {Genetic Algorithms with Sharing for Multimodal Function Optimization}, PAGES = {41--49}, } @INPROCEEDINGS{Shaefer1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Craig G. Shaefer}, TITLE = {The {A}{R}{G}{O}{T} Strategy: Adaptive Representation Genetic Optimizer Technique}, PAGES = {50--58}, } @INPROCEEDINGS{Goldberg1987c, CROSSREF = {Grefenstette1987}, AUTHOR = {David E. Goldberg and Robert E. Smith}, TITLE = {Nonstationary Function Optimization Using Genetic Algorithms with Dominance and Diploidy}, PAGES = {59--68}, } @INPROCEEDINGS{Antonisse1987, CROSSREF = {Grefenstette1987}, AUTHOR = {H. J. Antonisse and K. S. Keller}, TITLE = {Genetic Operators for High-Level Knowledge Representation}, PAGES = {69--76}, } @INPROCEEDINGS{Bickel1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Arthur S. Bickel and Riva Wenig Bickel}, TITLE = {Tree Structured Rules in Genetic Algorithms}, PAGES = {77--81}, } @INPROCEEDINGS{Holland1987, CROSSREF = {Grefenstette1987}, AUTHOR = {John H. Holland}, TITLE = {Genetic Algorithms and Classifier Systems: Foundations and Future Directions}, PAGES = {82--89}, } @INPROCEEDINGS{Liepins1987, CROSSREF = {Grefenstette1987}, AUTHOR = {G. E. Liepins and M. R. Hilliard and Mark Palmer and Michael Morrow}, TITLE = {Greedy Genetics}, PAGES = {90--99}, } @INPROCEEDINGS{Suh1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Jung Y. Suh and Dirk van Gucht}, TITLE = {Incorporating Heuristic Information into Genetic Search}, PAGES = {100--107}, } @INPROCEEDINGS{Whitley1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Darrell Whitley}, TITLE = {Using Reproductive Evaluation to Improve Genetic Search and Heuristic Discovery}, PAGES = {108--115}, } @INPROCEEDINGS{Sirag1987, CROSSREF = {Grefenstette1987}, AUTHOR = {David J. Sirag and Paul T. Weisser}, TITLE = {Toward a Unified Thermodynamic Genetic Operator}, PAGES = {116--122}, } @INPROCEEDINGS{Dolan1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Charles P. Dolan and Michael G. Dyer}, TITLE = {Toward the Evolution of Symbols}, PAGES = {123--131}, } @INPROCEEDINGS{Oosthuizen1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Deon G. Oosthuizen}, TITLE = {{S}{U}{P}{E}{R}{G}{R}{A}{N}: A Connectionist Approach to Learning, Integrating Genetic Algorithms and Graph Induction}, PAGES = {132--139}, } @INPROCEEDINGS{Robertson1987, CROSSREF = {Grefenstette1987}, AUTHOR = {George G. Robertson}, TITLE = {Parallel Implementation of Genetic Algorithms in a Classifier System}, PAGES = {140--147}, } @INPROCEEDINGS{Cohoon1987, CROSSREF = {Grefenstette1987}, AUTHOR = {J. P. Cohoon and S. U. Hedge and W. N. Martin and D. Richards}, TITLE = {Punctuated Equilibria: A Parallel Genetic Algorithm}, PAGES = {148--154}, } @INPROCEEDINGS{Pettey1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Chrisila B. Pettey and Michael R. Leuze and John J. Grefenstette}, TITLE = {A Parallel Genetic Algorithm}, PAGES = {155--161}, } @INPROCEEDINGS{Sannier1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Adrian V. Sannier II and Erik D. Goodman}, TITLE = {Genetic Learning Procedures in Distributed Environments}, PAGES = {162--169}, } @INPROCEEDINGS{Jog1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Prasanna Jog and Dirk Van Gucht}, TITLE = {Parallelisation of Probabilistic Sequential Search Algorithms}, PAGES = {170--176}, } @INPROCEEDINGS{Tanese1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Reiko Tanese}, TITLE = {Parallel Genetic Algorithms for a Hypercube}, PAGES = {177--183}, } @INPROCEEDINGS{Riolo1987a, CROSSREF = {Grefenstette1987}, AUTHOR = {Rick L. Riolo}, TITLE = {Bucket Brigade Performance: {I}. {L}ong Sequences of Classifiers}, PAGES = {184--195}, } @INPROCEEDINGS{Riolo1987b, CROSSREF = {Grefenstette1987}, AUTHOR = {Rick L. Riolo}, TITLE = {Bucket Brigade Performance: {I}{I}. {D}efault Hierarchies}, PAGES = {196--201}, } @INPROCEEDINGS{Grefenstette1987a, CROSSREF = {Grefenstette1987}, AUTHOR = {John J. Grefenstette}, TITLE = {Multilevel Credit Assignment in a Genetic Learning System}, PAGES = {202--209}, } @INPROCEEDINGS{DeJong1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Kenneth A. DeJong}, TITLE = {On Using Genetic Algorithms to Search Program Spaces}, PAGES = {210--216}, } @INPROCEEDINGS{Greene1987, CROSSREF = {Grefenstette1987}, AUTHOR = {David Perry Greene and Stephen F. Smith}, TITLE = {A Genetic System for Learning Models of Consumer Choice}, PAGES = {217--223}, } @INPROCEEDINGS{Oliver1987, CROSSREF = {Grefenstette1987}, AUTHOR = {I. M. Oliver and D. J. Smith and J. R. C. Holland}, TITLE = {A Study of Permutation Crossover Operators on the Traveling Salesman Problem}, PAGES = {224--230}, } @INPROCEEDINGS{Hilliard1987, CROSSREF = {Grefenstette1987}, AUTHOR = {M. R. Hilliard and G. E. Liepins and Mark Palmer and Michael Morrow and Jon Richardson}, TITLE = {A Classifier Based System for Discovering Scheduling Heuristics}, PAGES = {231--235}, } @INPROCEEDINGS{Fujiko1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Cory Fujiko and John Dickinson}, TITLE = {Using the Genetic Algorithm to Generate {L}{I}{S}{P} source code to solve the prisoner's dilemma}, PAGES = {236--240}, } @INPROCEEDINGS{Raghavan1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Vijay V. Raghavan and Brijesh Agarwal}, TITLE = {Optimal Determination of User-Oriented Clusters: An Application for the Reproductive Plan}, PAGES = {241--246}, } @INPROCEEDINGS{Wilson1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Stewart W. Wilson}, TITLE = {The Genetic Algorithm and Biological Development}, PAGES = {247--251}, } @INPROCEEDINGS{Davis1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Lawrence Davis and Susan Coombs}, TITLE = {Genetic Algorithms and Communication Link Speed Design: Theoretical Considerations}, PAGES = {252--256}, } @INPROCEEDINGS{Coombs1987, CROSSREF = {Grefenstette1987}, AUTHOR = {Susan Coombs and Lawrence Davis}, TITLE = {Genetic Algorithms and Communication Link Speed Design: Constraints and Operators}, PAGES = {257--260}, } @ARTICLE {Hajek1988, AUTHOR = {B. Hajek}, TITLE = {Cooling Schedules for Optimal Annealing}, JOURNAL = {Mathematics of Operations Research}, VOLUME = {13}, NUMBER = {2}, YEAR = {1988}, MONTH = {May}, PAGES = {311--329}, NOTE = {}, ABSTRACT = {}, } @TECHREPORT {Hartl1989, AUTHOR = {Richard F. Hartl}, TITLE = {A Global Convergence Proof for a Class of Genetic Algorithms}, INSTITUTION = {Institute of Econometrics, Operations Research and Systems Theory, Vienna University of Technology}, ADDRESS = {Argentinierstra{\ss}e 8, A-1040 Vienna, Austria}, YEAR = {1989}, TYPE = {Unpublished Manuscript}, NUMBER = {}, MONTH = {December}, NOTE = {Presented at the \"OGOR annual conference, Dec. 6th, 1989} } @ARTICLE {Holland1973, AUTHOR = {John H. Holland}, TITLE = {Genetic Algorithms and the Optimal Allocation of Trials}, JOURNAL = {SIAM Journal of Computing}, VOLUME = {2}, NUMBER = {2}, YEAR = {1973}, MONTH = {June}, PAGES = {88--105}, NOTE = {}, ABSTRACT = {}, } @BOOK {Holland1975, AUTHOR = {John H. Holland}, TITLE = {Adaptation in Natural and Artificial Systems}, PUBLISHER = {The University of Michigan Press}, ADDRESS = {Ann Arbor, Michigan}, YEAR = {1975}, VOLUME = {}, SERIES = {}, EDITION = {}, MONTH = {}, NOTE = {} } @BOOK {Holland1986, AUTHOR = {John H. Holland and Keith J. Holyoak and Richard E. Nisbett and Paul R. Thagard}, TITLE = {Induction: Processes of Inference, Learning, and Discovery}, PUBLISHER = {The MIT Press}, ADDRESS = {Cambridge, Massachusetts}, YEAR = {1986}, VOLUME = {}, SERIES = {Computational Models of Cognition and Perception}, EDITION = {}, MONTH = {}, NOTE = {} } @BOOK {Holland1992, AUTHOR = {John H. Holland}, TITLE = {Adaptation in Natural and Artificial Systems}, PUBLISHER = {The MIT Press}, ADDRESS = {Cambridge, Massachusetts}, YEAR = {1992}, VOLUME = {}, SERIES = {}, EDITION = {{T}he {M}{I}{T} {P}ress}, MONTH = {}, NOTE = {} } @BOOK {Holland1995, AUTHOR = {John H. Holland}, TITLE = {Hidden Order: How Adaptation Builds Complexity}, PUBLISHER = {Addison-Wesley}, ADDRESS = {Reading, Massachusetts}, YEAR = {1995}, VOLUME = {}, SERIES = {Helix Books}, EDITION = {}, MONTH = {}, NOTE = {} } @ARTICLE {Karr1991, AUTHOR = {Chuck Karr}, TITLE = {Genetic Algorithms for Fuzzy Controllers}, JOURNAL = {AI Expert}, VOLUME = {6}, NUMBER = {2}, YEAR = {1991}, MONTH = {February}, PAGES = {26--33}, NOTE = {}, ABSTRACT = {}, } @PROCEEDINGS{Kinnear1994, EDITOR = {Kenneth E. Kinnear}, BOOKTITLE = {Advances in Genetic Programming}, TITLE = {Advances in Genetic Programming}, YEAR = {1994}, MONTH = {}, VOLUME = {}, NUMBER = {}, SERIES = {Complex Adaptive Systems}, ORGANISATION = {}, PUBLISHER = {MIT Press}, ADDRESS = {Cambridge}, NOTE = {}, SIGNATURE = {WU Janko, 3144/A.0} } @INPROCEEDINGS{Kinnear1994a, CROSSREF = {Kinnear1994}, AUTHOR = {Kenneth E. Kinnear, Jr.}, TITLE = {A Perspective on the Work in this Book}, PAGES = {3--20}, } @INPROCEEDINGS{Koza1994a, CROSSREF = {Kinnear1994}, AUTHOR = {John R. Koza}, TITLE = {Introduction to Genetic Programming}, PAGES = {21--42}, } @INPROCEEDINGS{Altenberg1994, CROSSREF = {Kinnear1994}, AUTHOR = {Lee Altenberg}, TITLE = {The Evolution of Evolvability in Genetic Programming}, PAGES = {47--74}, } @INPROCEEDINGS{Angeline1994, CROSSREF = {Kinnear1994}, AUTHOR = {Peter J. Angeline}, TITLE = {Genetic Programming and Emergent Intelligence}, PAGES = {75--98}, } @INPROCEEDINGS{Koza1994b, CROSSREF = {Kinnear1994}, AUTHOR = {John R. Koza}, TITLE = {Scalable Learning in Genetic Programming using Automatic Function Definiton}, PAGES = {99--118}, } @INPROCEEDINGS{Kinnear1994b, CROSSREF = {Kinnear1994}, AUTHOR = {Kenneth E. Kinnear}, TITLE = {Alternatives in Automatic Function Definition: A Comparison in Performance}, PAGES = {119--142}, } @INPROCEEDINGS{Tackett1994, CROSSREF = {Kinnear1994}, AUTHOR = {Walter Alden Tackett and Aviram Carmi}, TITLE = {The Donut Problem: Scalability, Generalization and Breeding Policies in Genetic Programming}, PAGES = {143--176}, } @INPROCEEDINGS{Haeseleer1994, CROSSREF = {Kinnear1994}, AUTHOR = {Patrick D'Haeseleer and Jason Bluming}, TITLE = {Effects of Locality in Individual and Population Evolution}, PAGES = {177--198}, } @INPROCEEDINGS{Teller1994, CROSSREF = {Kinnear1994}, AUTHOR = {Astro Teller}, TITLE = {The Evolution of Mental Models}, PAGES = {199--220}, } @INPROCEEDINGS{Reynolds1994, CROSSREF = {Kinnear1994}, AUTHOR = {Craig W. Reynolds}, TITLE = {Evolution of Obstacle Avoidance Behavior: Using Noise to Promote Robust Solutions}, PAGES = {221--242}, } @INPROCEEDINGS{Ryan1994, CROSSREF = {Kinnear1994}, AUTHOR = {Conor Ryan}, TITLE = {Pygmies and Civil Servants}, PAGES = {243--264}, } @INPROCEEDINGS{Iba1994b, CROSSREF = {Kinnear1994}, AUTHOR = {Hitoshi Iba and Hugo de Garis and Taisuke Sato}, TITLE = {Genetic Programming Using a Minimum Description Length Principle}, PAGES = {265--284}, } @INPROCEEDINGS{Keith1994, CROSSREF = {Kinnear1994}, AUTHOR = {Mike J. Keith and Martin C. Martin}, TITLE = {Genetic Programming in C++: Implementation Issues}, PAGES = {285--310}, } @INPROCEEDINGS{Nordin1994, CROSSREF = {Kinnear1994}, AUTHOR = {Peter Nordin}, TITLE = {A Compiling Genetic Programming System that Directly Manipulates the Machine Code}, PAGES = {311--332}, } @INPROCEEDINGS{Spencer1994, CROSSREF = {Kinnear1994}, AUTHOR = {Graham Spencer}, TITLE = {Automatic Generation of Programs for Crawling and Walking}, PAGES = {335--354}, } @INPROCEEDINGS{Andrews1994, CROSSREF = {Kinnear1994}, AUTHOR = {Martin Andrews and Richard Prager}, TITLE = {Genetic Programming for the Acquisition of Double Auction Market Strategies}, PAGES = {355--368}, } @INPROCEEDINGS{Oakley1994, CROSSREF = {Kinnear1994}, AUTHOR = {Howard Oakley}, TITLE = {Two Scientific Applications of Genetic Programming: Stack Filters and Non-Linear Equation Fitting to Chaotic Data}, PAGES = {369--390}, } @INPROCEEDINGS{Handley1994, CROSSREF = {Kinnear1994}, AUTHOR = {Simon G. Handley}, TITLE = {The Automatic Generation of Plans for a Mobile Robot via Genetic Programming with Automatically Defined Functions}, PAGES = {391--408}, } @INPROCEEDINGS{Siegel1994, CROSSREF = {Kinnear1994}, AUTHOR = {Eric V. Siegel}, TITLE = {Competitively Evolving Decision Trees Against Fixed Training Cases for Natural Language Processing}, PAGES = {409--424}, } @INPROCEEDINGS{Jannink1994, CROSSREF = {Kinnear1994}, AUTHOR = {Jan Jannink}, TITLE = {Cracking and Co-Evolving Randomizers}, PAGES = {425--444}, } @INPROCEEDINGS{Masand1994, CROSSREF = {Kinnear1994}, AUTHOR = {Brij Masand}, TITLE = {Optimizing Confidence of Text Classification by Evolution of Symbolic Expressions}, PAGES = {445--458}, } @INPROCEEDINGS{Nguyen1994, CROSSREF = {Kinnear1994}, AUTHOR = {Thang Nguyen and Thomas Huang}, TITLE = {Evolvable 3{D} Modeling for Model-Based Object Recognition Systems}, PAGES = {459--476}, } @INPROCEEDINGS{Andre1994, CROSSREF = {Kinnear1994}, AUTHOR = {David Andre}, TITLE = {Automatically Defined Features: The Simultaneous Evolution of 2-Dimensional Feature Detectors and an Algorithm for Using Them}, PAGES = {477--494}, } @INPROCEEDINGS{Gruau1994, CROSSREF = {Kinnear1994}, AUTHOR = {Fr\'{e}d\'{e}ric Gruau}, TITLE = {Genetic Micro Programming of Neural Networks}, PAGES = {495--518}, } @ARTICLE {Kitano1990, AUTHOR = {Hiroaki Kitano}, TITLE = {Designing Neural Networks Using Genetic Algorithms with Graph Generation System}, JOURNAL = {Complex Systems}, VOLUME = {4}, NUMBER = {4}, YEAR = {1990}, MONTH = {}, PAGES = {461--476}, NOTE = {}, ABSTRACT = {}, } @TECHREPORT {Koza1990, AUTHOR = {John R. Koza}, TITLE = {Genetic Programming: A Paradigm for Genetically Breeding Populations of Computer Programs to Solve Problems}, INSTITUTION = {Department of Computer Science, Stanford University}, ADDRESS = {Stanford, California 94305}, YEAR = {1990}, TYPE = {}, NUMBER = {STAN-CS-90-1314}, MONTH = {June}, NOTE = {} } @BOOK {Koza1992, AUTHOR = {John R. Koza}, TITLE = {Genetic Programming: On the Programming of Computers by Means of Natural Selection}, PUBLISHER = {The MIT Press}, ADDRESS = {Cambridge, Massachusetts}, YEAR = {1992}, VOLUME = {}, SERIES = {}, EDITION = {}, MONTH = {}, NOTE = {}, SIGNATURE = {Uni Wien, Trappl, B 30788} } @BOOK {Koza1994c, AUTHOR = {John R. Koza}, TITLE = {Genetic Programming II: Automatic Discovery of Reusable Programs}, PUBLISHER = {The MIT Press}, ADDRESS = {Cambridge, Massachusetts}, YEAR = {1994}, VOLUME = {}, SERIES = {}, EDITION = {}, MONTH = {}, NOTE = {}, SIGNATURE = {WU Wien, Panny, 383 E/I.2} } @PROCEEDINGS{Michalski1986, EDITOR = {Ryszard S. Michalski and Jaime G. Carbonell and Tom M. Mitchell}, BOOKTITLE = {Machine Learning}, TITLE = {Machine Learning}, YEAR = {1986}, MONTH = {}, VOLUME = {II}, NUMBER = {}, SERIES = {}, ORGANISATION = {}, PUBLISHER = {Morgan Kaufmann}, ADDRESS = {Los Altos}, NOTE = {}, SIGNATURE = {WU, Janko, 957/I.2} } @INPROCEEDINGS{Holland1986a, CROSSREF = {Michalski1986}, AUTHOR = {John H. Holland}, TITLE = {Escaping Brittleness: The Possibilities of General--Purpose Learning Algorithms Applied to Parallel Rule-Based Systems}, PAGES = {593--623}, } @BOOK {Otten1989, AUTHOR = {R. H. J. M. Otten and L. P. P. P. van Ginneken}, TITLE = {The Annealing Algorithm}, PUBLISHER = {Kluwer Academic Publishers}, ADDRESS = {Boston}, YEAR = {1989}, VOLUME = {SECS72}, SERIES = {The Kluwer International Series in Engineering and Computer Science. VLSI, Computer Architecture, and Digital Signal Processing}, EDITION = {}, MONTH = {}, NOTE = {WUW AI: I.2/1561} } @PROCEEDINGS{Rawlins1991, EDITOR = {Gregory J.E. Rawlins}, BOOKTITLE = {Foundations of Genetic Algorithms}, TITLE = {Foundations of Genetic Algorithms}, YEAR = {1991}, MONTH = {}, VOLUME = {}, NUMBER = {}, SERIES = {}, ORGANISATION = {}, PUBLISHER = {Morgan Kaufmann}, ADDRESS = {San Mateo}, NOTE = {}, SIGNATURE = {WU, Panny, 315E/I.2} } @INPROCEEDINGS{Bridges1991, CROSSREF = {Rawlins1991}, AUTHOR = {Clayton L. Bridges and David E. Goldberg}, TITLE = {The Nonuniform Walsh-Schema Transform}, PAGES = {13--22}, } @INPROCEEDINGS{Davidor1991b, CROSSREF = {Rawlins1991}, AUTHOR = {Yuval Davidor}, TITLE = {Epistasis Variance: A Viewpoint on GA-Hardness}, PAGES = {23--35}, } @INPROCEEDINGS{Liepins1991c, CROSSREF = {Rawlins1991}, AUTHOR = {Gunar E. Liepins and Michael D. Vose}, TITLE = {Deceptiveness and Genetic Algorithm Dynamics}, PAGES = {36--50}, } @INPROCEEDINGS{Ankenbrandt1991, CROSSREF = {Rawlins1991}, AUTHOR = {Carol A. Ankenbrandt}, TITLE = {An Extension to the Theory of Convergence and a Proof of the Time Complexity of Genetic Algorithms}, PAGES = {53--68}, } @INPROCEEDINGS{Goldberg1991a, CROSSREF = {Rawlins1991}, AUTHOR = {David E. Goldberg and Kalyanmoy Deb}, TITLE = {A Comparative Analysis of Selection Schemes Used in Genetic Algorithms}, PAGES = {69--93}, } @INPROCEEDINGS{Syswerda1991c, CROSSREF = {Rawlins1991}, AUTHOR = {Gilbert Syswerda}, TITLE = {A Study of Reproduction in Generational and Steady State Genetic Algorithms}, PAGES = {94--101}, } @INPROCEEDINGS{Schaffer1991a, CROSSREF = {Rawlins1991}, AUTHOR = {J. David Schaffer and Larry J. Eshelman and Daniel Offut}, TITLE = {Spurious Correlations and Premature Convergence in Genetic Algorithms}, PAGES = {102--112}, } @INPROCEEDINGS{Booker1991, CROSSREF = {Rawlins1991}, AUTHOR = {Lashon B. Booker}, TITLE = {Representing Attribute-Based Concepts in a Classifier System}, PAGES = {115--127}, } @INPROCEEDINGS{Westerdale1991a, CROSSREF = {Rawlins1991}, AUTHOR = {T. H. Westerdale}, TITLE = {Quasimorphisms or Queasymorphisms? Modeling Finite Automaton Environments}, PAGES = {128--147}, } @INPROCEEDINGS{Smith1991a, CROSSREF = {Rawlins1991}, AUTHOR = {Robert E. Smith and David E. Goldberg}, TITLE = {Variable Default Hierarchy Separation in a Classifier System}, PAGES = {148--167}, } @INPROCEEDINGS{Koza1991a, CROSSREF = {Rawlins1991}, AUTHOR = {John R. Koza}, TITLE = {A Hierarchical Approach to Learning the Boolean Multiplexer Function}, PAGES = {171--192}, } @INPROCEEDINGS{Antonisse1991, CROSSREF = {Rawlins1991}, AUTHOR = {H. James Antonisse}, TITLE = {A Grammar-Based Genetic Algorithm}, PAGES = {193--204}, } @INPROCEEDINGS{Wright1991, CROSSREF = {Rawlins1991}, AUTHOR = {Alden H. Wright}, TITLE = {Genetic Algorithms for Real Parameter Optimizations}, PAGES = {205--218}, } @INPROCEEDINGS{Whitley1991c, CROSSREF = {Rawlins1991}, AUTHOR = {L. Darrell Whitley}, TITLE = {Fundamental Principles of Deception in Genetic Search}, PAGES = {221--241}, } @INPROCEEDINGS{Battle1991, CROSSREF = {Rawlins1991}, AUTHOR = {David L. Battle and Michael D. Vose}, TITLE = {Isomorphisms of Genetic Algorithms}, PAGES = {242--251}, } @INPROCEEDINGS{Grefenstette1991c, CROSSREF = {Rawlins1991}, AUTHOR = {John J. Grefenstette}, TITLE = {Conditions for Implicit Parallelism}, PAGES = {252--261}, } @INPROCEEDINGS{Eshelman1991a, CROSSREF = {Rawlins1991}, AUTHOR = {Larry J. Eshelman}, TITLE = {The {C}{H}{C} Adaptive Search Algorithm: How to Have Safe Search When Engaging in Nontraditional Genetic Recombination}, PAGES = {265--283}, } @INPROCEEDINGS{Fox1991, CROSSREF = {Rawlins1991}, AUTHOR = {B. R. Fox and M. B. McMahon}, TITLE = {Genetic Operators for Sequencing Problems}, PAGES = {284--300}, } @INPROCEEDINGS{Spears1991a, CROSSREF = {Rawlins1991}, AUTHOR = {William M. Spears and Kennth A. DeJong}, TITLE = {An Analysis of Multi-Point Crossover}, PAGES = {301--315}, } @INPROCEEDINGS{Muehlenbein1991a, CROSSREF = {Rawlins1991}, AUTHOR = {Heinz M{\"u}lenbein}, TITLE = {Evolution in Time and Space -- The Parallel Genetic Algorithm}, PAGES = {316--337}, } @BOOK {Rechenberg1973, AUTHOR = {Ingo Rechenberg}, TITLE = {Evolutionsstrategie}, PUBLISHER = {Friedrich Frommann Verlag (G\"unther Holzboog KG)}, ADDRESS = {Stuttgart}, YEAR = {1973}, VOLUME = {15}, SERIES = {problemata}, EDITION = {}, MONTH = {}, NOTE = {} } @BOOK {Rechenberg1994, AUTHOR = {Ingo Rechenberg}, TITLE = {Evolutionsstrategie'94}, PUBLISHER = {Friedrich Frommann Verlag (G\"unther Holzboog KG)}, ADDRESS = {Stuttgart}, YEAR = {1994}, VOLUME = {1}, SERIES = {Werkstatt Bionik und Evolutionstechnik}, EDITION = {}, MONTH = {}, NOTE = {}, SIGNATURE = {WU Janko, 3027/A.0} } @ARTICLE {Robbins1952, AUTHOR = {Herbert Robbins}, TITLE = {Some Aspects of the Sequential Design of Experiments}, JOURNAL = {Bulletin of the American Mathematical Society}, VOLUME = {58}, NUMBER = {}, YEAR = {1952}, MONTH = {September}, PAGES = {527--535}, NOTE = {}, ABSTRACT = {}, } @PROCEEDINGS{Schaffer1989, EDITOR = {J. David Schaffer}, BOOKTITLE = {Proceedings of the Third International Conference on Genetic Algorithms}, TITLE = {Proceedings of the Third International Conference on Genetic Algorithms (ICGA'89)}, YEAR = {1989}, MONTH = {}, VOLUME = {}, NUMBER = {}, SERIES = {}, ORGANISATION = {George Mason University}, PUBLISHER = {Morgan Kaufmann Publishers, Inc.}, ADDRESS = {San Mateo, California}, NOTE = {} } @INPROCEEDINGS{Syswerda1989, CROSSREF = {Schaffer1989}, AUTHOR = {Gilbert Syswerda}, TITLE = {Uniform Crossover in Genetic Algorithms}, PAGES = {2--9}, } @INPROCEEDINGS{Eshelman1989, CROSSREF = {Schaffer1989}, AUTHOR = {Larry J. Eshelman and Richard A. Caruana and J. David Schaffer}, TITLE = {Biases in the Crossover Landscape}, PAGES = {10--19}, } @INPROCEEDINGS{Grefenstette1989a, CROSSREF = {Schaffer1989}, AUTHOR = {John J. Grefenstette and James E. Baker}, TITLE = {How Genetic Algorithms Work: A Critical Look at Implicit Parallelism}, PAGES = {20--27}, } @INPROCEEDINGS{Ros1989, CROSSREF = {Schaffer1989}, AUTHOR = {Hans Ros}, TITLE = {Some Results on Boolean Concept Learning by Genetic Algorithms}, PAGES = {28--33}, } @INPROCEEDINGS{Belew1989a, CROSSREF = {Schaffer1989}, AUTHOR = {Richard K. Belew}, TITLE = {When Both Individuals and Populations Search: Adding Simple Learning to the Genetic Algorithm}, PAGES = {34--41}, } @INPROCEEDINGS{Deb1989, CROSSREF = {Schaffer1989}, AUTHOR = {Kalyanmoy Deb and David E. Goldberg}, TITLE = {An Investigation of Niche and Species Formation in Genetic Function Optimization}, PAGES = {42--50}, } @INPROCEEDINGS{Schaffer1989a, CROSSREF = {Schaffer1989}, AUTHOR = {J. David Schaffer and Richard A. Caruana and Larry J. Eshelman and Rajarshi Das}, TITLE = {A Study of Control Parameters Affecting Online Performance of Genetic Algorithms for Function Optimization}, PAGES = {51--60}, } @INPROCEEDINGS{Davis1989a, CROSSREF = {Schaffer1989}, AUTHOR = {Lawrence Davis}, TITLE = {Adapting Operator Probabilities in Genetic Algorithms}, PAGES = {61--69}, } @INPROCEEDINGS{Goldberg1989a, CROSSREF = {Schaffer1989}, AUTHOR = {David E. Goldberg}, TITLE = {Sizing Populations for Serial and Parallel Genetic Algorithms}, PAGES = {70--79}, } @INPROCEEDINGS{Goldberg1989b, CROSSREF = {Schaffer1989}, AUTHOR = {David E. Goldberg}, TITLE = {Zen and the Art of Genetic Algorithms}, PAGES = {80--85}, } @INPROCEEDINGS{Antonisse1989, CROSSREF = {Schaffer1989}, AUTHOR = {Jim Antonisse}, TITLE = {A New Interpretation of Schema Notation that Overturns the Binary Encoding}, PAGES = {86--91}, } @INPROCEEDINGS{Chi1989, CROSSREF = {Schaffer1989}, AUTHOR = {Ping-Chung Chi}, TITLE = {Genetic Search with Proportion Estimations}, PAGES = {92--97}, } @INPROCEEDINGS{Davidor1989, CROSSREF = {Schaffer1989}, AUTHOR = {Yuval Davidor}, TITLE = {Analogous Crossover}, PAGES = {98--103}, } @INPROCEEDINGS{Fogarty1989, CROSSREF = {Schaffer1989}, AUTHOR = {Terence C. Fogarty}, TITLE = {Varying the Probability of Mutation in the Genetic Algorithm}, PAGES = {104--109}, } @INPROCEEDINGS{Jog1989, CROSSREF = {Schaffer1989}, AUTHOR = {Prasanna Jog and Jung Y. Suh and Dirk van Gucht}, TITLE = {The Effects of Population Size, Heuristic Crossover and Local Improvement on a Genetic Algorithm for the Traveling Salesman Problem}, PAGES = {110--115}, } @INPROCEEDINGS{Whitley1989a, CROSSREF = {Schaffer1989}, AUTHOR = {Darrell Whitley}, TITLE = {The {G}{E}{N}{I}{T}{O}{R} Algorithm and Selection Pressure: Why Rank-Based Allocation of Reproductive Trials is Best}, PAGES = {116--123}, } @INPROCEEDINGS{DeJong1989, CROSSREF = {Schaffer1989}, AUTHOR = {Kenneth A. DeJong and William M. Spears}, TITLE = {Using Genetic Algorithms to Solve {N}{P}-Complete Problems}, PAGES = {124--132}, } @INPROCEEDINGS{Whitley1989b, CROSSREF = {Schaffer1989}, AUTHOR = {Darrell Whitley and Timothy Starkwater and D'Ann Fuquay}, TITLE = {Scheduling Problems and Traveling Salesmen: The Genetic Edge Recombination Operator}, PAGES = {133--140}, } @INPROCEEDINGS{Siedlecki1989, CROSSREF = {Schaffer1989}, AUTHOR = {W. Siedlecki and J. Sklansky}, TITLE = {Constrained Genetic Optimization via Dynamic Reward-Penalty Balancing and Its Use in Pattern Recognition}, PAGES = {141--150}, } @INPROCEEDINGS{Powell1989, CROSSREF = {Schaffer1989}, AUTHOR = {David J. Powell and Siu Shing Tong and Michael M. Skolnick}, TITLE = {En{G}{E}{N}{E}ous Domain Independent, Machine Learning for Design Optimization}, PAGES = {151--159}, } @INPROCEEDINGS{Cleveland1989, CROSSREF = {Schaffer1989}, AUTHOR = {Gary A. Cleveland and Stephen F. Smith}, TITLE = {Using Genetic Algorithms to Schedule Flow Shop Releases}, PAGES = {160--169}, } @INPROCEEDINGS{Lucasius1989, CROSSREF = {Schaffer1989}, AUTHOR = {C. B. Lucasius and G. Kateman}, TITLE = {Application of Genetic Algorithms in Chemometrics}, PAGES = {170--176}, } @INPROCEEDINGS{Odetayo1989, CROSSREF = {Schaffer1989}, AUTHOR = {M. O. Odetayo and D. R. McGregor}, TITLE = {Genetic Algorithms for Inducing Control Rules for a Dynamic System}, PAGES = {177--182}, } @INPROCEEDINGS{Grefenstette1989b, CROSSREF = {Schaffer1989}, AUTHOR = {John J. Grefenstette}, TITLE = {A System for Learning Control Strategies with Genetic Algorithms}, PAGES = {183--190}, } @INPROCEEDINGS{Richardson1989, CROSSREF = {Schaffer1989}, AUTHOR = {Jon T. Richardson and Mark R. Palmer and Gunar E. Liepins and Mike Hilliard}, TITLE = {Some Guidelines for Genetic Algorithms with Penalty Functions}, PAGES = {191--197}, } @INPROCEEDINGS{Marks1989, CROSSREF = {Schaffer1989}, AUTHOR = {Robert E. Marks}, TITLE = {Breeding Hybrid Strategies: Optimal Behavior for Oligopolists}, PAGES = {198--207}, } @INPROCEEDINGS{Maza1989, CROSSREF = {Schaffer1989}, AUTHOR = {Michael de la Maza}, TITLE = {A {S}{E}{A}{G}{U}{L} Visits the Race Track}, PAGES = {208--212}, } @INPROCEEDINGS{Bramlette1989, CROSSREF = {Schaffer1989}, AUTHOR = {Mark F. Bramlette and Rod Cusic}, TITLE = {A Comparative Evaluation of Search Methods Applied to Parametric Design of Aircraft}, PAGES = {213--218}, } @INPROCEEDINGS{Chu1989, CROSSREF = {Schaffer1989}, AUTHOR = {Chee-Hung Henry Chu}, TITLE = {A Genetic Approach to the Configuration of Stack Filters}, PAGES = {219--224}, } @INPROCEEDINGS{Huynen1989, CROSSREF = {Schaffer1989}, AUTHOR = {Martijn A. Huynen and Paulien Hogeweg}, TITLE = {Genetic Algorithms amd Information Accumulation during the Evolution of Gene Regulation}, PAGES = {225--230}, } @INPROCEEDINGS{Hesser1989, CROSSREF = {Schaffer1989}, AUTHOR = {J. Hesser and R. M\"anner and O. Stucky}, TITLE = {Optimization of {S}teiner Trees Using Genetic Algorithms}, PAGES = {231--236}, } @INPROCEEDINGS{Hintz1989, CROSSREF = {Schaffer1989}, AUTHOR = {Kenneth J. Hintz}, TITLE = {Procedure Learning Using a Variable-Dimension Solution Space}, PAGES = {237--243}, } @INPROCEEDINGS{Wilson1989, CROSSREF = {Schaffer1989}, AUTHOR = {Stewart W. Wilson and David E. Goldberg}, TITLE = {A Critical Review of Classifier Systems}, PAGES = {244--255}, } @INPROCEEDINGS{Riolo1989a, CROSSREF = {Schaffer1989}, AUTHOR = {Rick L. Riolo}, TITLE = {The Emergence of Coupled Sequences of Classifiers}, PAGES = {256--264}, } @INPROCEEDINGS{Booker1989, CROSSREF = {Schaffer1989}, AUTHOR = {Lashon B. Booker}, TITLE = {Triggered Rule Discovery in Classifier Systems}, PAGES = {265--274}, } @INPROCEEDINGS{Belew1989b, CROSSREF = {Schaffer1989}, AUTHOR = {Richard K. Belew and Michael Gherrity}, TITLE = {Back Propagation for the Classifier System}, PAGES = {275--281}, } @INPROCEEDINGS{Westerdale1989, CROSSREF = {Schaffer1989}, AUTHOR = {T. H. Westerdale}, TITLE = {A Defense of the Bucket Brigade}, PAGES = {282--290}, } @INPROCEEDINGS{Zhou1989, CROSSREF = {Schaffer1989}, AUTHOR = {Hayong Harry Zhou and John J. Grefenstette}, TITLE = {Learning by Analogy in Genetic Classifier Systems}, PAGES = {291--297}, } @INPROCEEDINGS{Compiani1989, CROSSREF = {Schaffer1989}, AUTHOR = {M. Compiani and D. Montanari and R. Serra and P. Simonini}, TITLE = {Asymptotic Dynamics of Classifier Systems}, PAGES = {298--303}, } @INPROCEEDINGS{JMiller1989, CROSSREF = {Schaffer1989}, AUTHOR = {John H. Miller and Stephanie Forrest}, TITLE = {The Dynamical Behavior of Classifier Systems}, PAGES = {304--310}, } @INPROCEEDINGS{Huang1989, CROSSREF = {Schaffer1989}, AUTHOR = {Dijia Huang}, TITLE = {The Context-Array Bucket-Brigade Algorithm: An Enhanced Approach to Credit-Apportionment in Classifier Systems}, PAGES = {311--316}, } @INPROCEEDINGS{Roberts1989, CROSSREF = {Schaffer1989}, AUTHOR = {Gary Roberts}, TITLE = {A Rational Reconstruction of {W}ilson's {A}nimat and {H}olland's {C}{S}-1}, PAGES = {317--321}, } @INPROCEEDINGS{Riolo1989b, CROSSREF = {Schaffer1989}, AUTHOR = {Rick L. Riolo}, TITLE = {The Emergence of Default Hierarchies in Learning Classifier Systems}, PAGES = {322--327}, } @INPROCEEDINGS{Schuurmans1989, CROSSREF = {Schaffer1989}, AUTHOR = {Dale Schuurmans and Jonathan Schaeffer}, TITLE = {Representational Difficulties with Classifier Systems}, PAGES = {328--333}, } @INPROCEEDINGS{Shu1989, CROSSREF = {Schaffer1989}, AUTHOR = {Lingyan Shu and Jonathan Schaeffer}, TITLE = {{V}{C}{S}: Variable Classifier Systems}, PAGES = {334--339}, } @INPROCEEDINGS{RSmith1989, CROSSREF = {Schaffer1989}, AUTHOR = {Robert E. Smith and Manuel Valenzuela-Rend\'{o}n}, TITLE = {A Study of Rule Set Development in a Learning Classifier System}, PAGES = {340--346}, } @INPROCEEDINGS{StSmith1989, CROSSREF = {Schaffer1989}, AUTHOR = {Stephen J. Smith and Stewart W. Wilson}, TITLE = {Rosetta: Toward a Model of Learning Problems}, PAGES = {347--350}, } @INPROCEEDINGS{Rendon1989, CROSSREF = {Schaffer1989}, AUTHOR = {Manuel Valenzuela-Rend\'{o}n}, TITLE = {Boolean Analysis of Classifier Sets}, PAGES = {351--359}, } @INPROCEEDINGS{Harp1989, CROSSREF = {Schaffer1989}, AUTHOR = {Steven Alex Harp and Tariq Samad and Aloke Guha}, TITLE = {Towards the Genetic Synthesis of Neural Networks}, PAGES = {360--369}, } @INPROCEEDINGS{Caudell1989, CROSSREF = {Schaffer1989}, AUTHOR = {Thomas P. Caudell and Charles P. Dolan}, TITLE = {Parametric Connectivity: Training of Constrained Networks Using Genetic Algorithms}, PAGES = {370--374}, } @INPROCEEDINGS{Davis1989b, CROSSREF = {Schaffer1989}, AUTHOR = {Lawrence Davis}, TITLE = {Mapping Neural Networks into Classifier Systems}, PAGES = {375--378}, } @INPROCEEDINGS{GMiller1989, CROSSREF = {Schaffer1989}, AUTHOR = {Geoffrey F. Miller and Peter M. Todd and Shailesh U. Hedge}, TITLE = {Designing Neural Networks Using Genetic Algorithms}, PAGES = {379--384}, } @INPROCEEDINGS{Oosthuizen1989, CROSSREF = {Schaffer1989}, AUTHOR = {G. Deon Oosthuizen}, TITLE = {Machine Learning: A Mathematical Framework for Neural Network, Symbolic and Genetics-Based Learning}, PAGES = {385--390}, } @INPROCEEDINGS{Whitley1989c, CROSSREF = {Schaffer1989}, AUTHOR = {Darrell Whitley and Thomas Hanson}, TITLE = {Optimizing Neural Networks Using Faster, More Accurate Genetic Search}, PAGES = {391--397}, } @INPROCEEDINGS{Pettey1989, CROSSREF = {Schaffer1989}, AUTHOR = {Chrisila C. Pettey and Michael R. Leuze}, TITLE = {A Theoretical Investigation of a Parallel Genetic Algorithm}, PAGES = {398--405}, } @INPROCEEDINGS{Brown1989, CROSSREF = {Schaffer1989}, AUTHOR = {Donald E. Brown and Christopher L. Huntley and Andrew R. Spillane}, TITLE = {A Parallel Genetic Heuristic for the Quadratic Assignment Problem}, PAGES = {406--415}, } @INPROCEEDINGS{Muehlenbein1989, CROSSREF = {Schaffer1989}, AUTHOR = {H. M\"uhlenbein}, TITLE = {Parallel Genetic Algorithms, Population Genetics and Combinatorial Optimization}, PAGES = {416--421}, } @INPROCEEDINGS{Schleuter1989, CROSSREF = {Schaffer1989}, AUTHOR = {Martina Gorges-Schleuter}, TITLE = {{A}{S}{P}{A}{R}{A}{G}{O}{S} An Asynchronous Parallel Genetic Optimization Strategy}, PAGES = {422--427}, } @INPROCEEDINGS{Manderick1989, CROSSREF = {Schaffer1989}, AUTHOR = {Bernard Manderick and Piet Spiessens}, TITLE = {Fine-Grained Parallel Genetic Algorithms}, PAGES = {428--433}, } @INPROCEEDINGS{Tanese1989, CROSSREF = {Schaffer1989}, AUTHOR = {Reiko Tanese}, TITLE = {Distributed Genetic Algorithms}, PAGES = {434--440}, } @BOOK {Schwefel1977, AUTHOR = {Hans Paul Schwefel}, TITLE = {Numerische Optimierung von Computer Modellen mittels der Evolutionsstrategie}, PUBLISHER = {Birkh\"auser Verlag}, ADDRESS = {Basel}, YEAR = {1977}, VOLUME = {26}, SERIES = {Interdisciplinary systems research}, EDITION = {}, MONTH = {}, NOTE = {} } @PROCEEDINGS{Schwefel1991, EDITOR = {H.-P. Schwefel and R. M\"anner}, BOOKTITLE = {Parallel Problem Solving from Nature}, TITLE = {Parallel Problem Solving from Nature}, YEAR = {1991}, MONTH = {}, VOLUME = {496}, NUMBER = {}, SERIES = {Lecture Notes in Computer Science}, ORGANISATION = {FB Informatik-Systemanalyse, Universit\"at Dortmund}, PUBLISHER = {Springer}, ADDRESS = {Berlin}, NOTE = {}, SIGNATURE = {WU Janko, 2589/G.1} } @INPROCEEDINGS{Eiben1991, CROSSREF = {Schwefel1991}, AUTHOR = {A. E. Eiben and E. H.L. Aarts and K. M. VanHee}, TITLE = {Global Convergence of Genetic Algorithms: A Markov Chain Analysis}, PAGES = {4--12}, } @INPROCEEDINGS{Goldberg1991b, CROSSREF = {Schwefel1991}, AUTHOR = {David E. Goldberg}, TITLE = {The Theory of Virtual Alphabets}, PAGES = {13--22}, } @INPROCEEDINGS{Hesser1991, CROSSREF = {Schwefel1991}, AUTHOR = {J\"urgen Hesser and Reinhard M\"anner}, TITLE = {Towards an Optimal Mutation Probability for Genetic Algorithms}, PAGES = {23--32}, } @INPROCEEDINGS{Hesser1991a, CROSSREF = {Schwefel1991}, AUTHOR = {J\"urgen Hesser and Reinhard M\"anner}, TITLE = {An Alternative Genetic Algorithm}, PAGES = {33--47}, } @INPROCEEDINGS{DeJong1991, CROSSREF = {Schwefel1991}, AUTHOR = {Kenneth A. De Jong and Wiiliam M. Spears}, TITLE = {An Analysis of the Interacting Roles of Population Size and Crossover in Genetic Algorithms}, PAGES = {38--47}, } @INPROCEEDINGS{Blume1991, CROSSREF = {Schwefel1991}, AUTHOR = {Christian Blume}, TITLE = {{G}{L}{E}{A}{M} -- A System for Simulated ``Intuitive Learning''}, PAGES = {48--54}, } @INPROCEEDINGS{Colorni1991, CROSSREF = {Schwefel1991}, AUTHOR = {Alberto Colorni and Marco Dorigo and Vittorio Maniezzo}, TITLE = {Genetic Algorithms and Highly Constrained Problems: The Time--Table Case}, PAGES = {55--59}, } @INPROCEEDINGS{Davidor1991c, CROSSREF = {Schwefel1991}, AUTHOR = {Yuval Davidor and Yaron Goldberg}, TITLE = {An Evolution Standing on the Design of Redundant Manipulators}, PAGES = {60--69}, } @INPROCEEDINGS{Gerrits1991, CROSSREF = {Schwefel1991}, AUTHOR = {Marleen Gerrits and Paulien Hogeweg}, TITLE = {Redundant Coding of an {N}{P}-complete Problem Allows Effective Genetic Algorithm Search}, PAGES = {70--74}, } @INPROCEEDINGS{Hulin1991b, CROSSREF = {Schwefel1991}, AUTHOR = {Martin Hulin}, TITLE = {Circuit Partitioning with Genetic Algorithms Using a Coding Scheme to Preserve the Structure of a Circuit}, PAGES = {75--79}, } @INPROCEEDINGS{Husbands1991b, CROSSREF = {Schwefel1991}, AUTHOR = {Philip Husbands and Frank Mill and Stephen Warrington}, TITLE = {Genetic Algorithms, Production Plan Optimisation and Scheduling}, PAGES = {80--84}, } @INPROCEEDINGS{Johnson1991, CROSSREF = {Schwefel1991}, AUTHOR = {Timothy Johnson and Philip Husbands}, TITLE = {System Identification Using Genetic Algorithms}, PAGES = {85--89}, } @INPROCEEDINGS{Lucasius1991a, CROSSREF = {Schwefel1991}, AUTHOR = {C. 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Smith", title = "A Memetic Algorithm to Schedule Grid Maintenance", booktitle = "Proceedings of the International Conference on Computational Intelligence for Modelling Control and Automation, Vienna: Evolutionary Computation and Fuzzy Logic for Intelligent Control, Knowledge Acquisition and Information Retrieval", pages = "122--127", year ="1999", publisher = "IOS Press 1999" } @InProceedings{DeCausmaecker_VandenBerghe_Burke_99, author = "P. de Causmaecker and G. van den Berghe and E.K. Burke", title = "Using Tabu Search as a Local Heuristic in a Memetic Algorithm for the Nurse Rostering Problem", booktitle = "Proceedings of the Thirteenth Conference on Quantitative Methods for Decision Making", address = "Brussels, Belgium", pages = "abstract only, poster presentation", year ="1999", publisher = "" } @InProceedings{Ozcan_Mohan_98, author = "E. Ozcan and C.K. Mohan", title = "Steady State Memetic Algorithm for Partial Shape Matching", booktitle = "Evolutionary Programming VII", editor = "V.W. Porto and N. Saravanan and D. Waagen", pages = "527--536", series = "Lecture Notes in Computer Science", year = "1998", publisher = "Springer, Berlin", volume = "1447" } @InProceedings{icga97*458, author = "Christine L. Valenzuela and L. P. Williams", title = "Improving Heuristic Algorithms for the {Travelling Salesman Problem} by Using a Genetic Algorithm to Perturb the Cities", pages = "458--464", ISBN = "1-55860-487-1", editor = "Thomas B{\"a}ck", booktitle = "Proceedings of the 7th International Conference on Genetic Algorithms", publisher = "Morgan Kaufmann", address = "San Francisco", year = "1997" } @InProceedings{rana.howe-1996:compaheuri:inbook:174, author = "Soraya Rana and Adele E. Howe and L. Darrell Whitley and Keith Mathias", title = "Comparing Heuristic, Evolutionary and Local Search Approaches to Scheduling", editor = "B. Drabble", booktitle = "Proceedings of the 3rd International Conference on Artificial Intelligence Planning Systems (AIPS-96)", year = "1996", publisher = "AAAI Press", pages = "174--181" } @InCollection{ling1992, author = "S. E. Ling", title = "Integrating Genetic Algorithms with a Prolog Assignment Program as a Hybrid Solution for a Polytechnic Timetable Problem", booktitle = "Parallel Problem Solving from Nature II", pages = "321--329", publisher = "Elsevier Science Publisher B. V.", year = "1992" } @InProceedings{icga95*122, author = "James Bowen and Gerry Dozier", title = "Solving Constraint Satisfaction Problems Using a Genetic/Systematic Search Hybrid That Realizes When to Quit", pages = "122--129", ISBN = "1-55860-370-0", editor = "Larry J. Eshelman", booktitle = "Proceedings of the 6th International Conference on Genetic Algorithms", publisher = "Morgan {K}aufmann Publishers", address = "San Francisco", year = "1995" } @InProceedings{icga95*174, author = "James M. Varanelli and James P. Cohoon", title = "Population-Oriented Simulated Annealing: {A} Genetic/Thermodynamic Hybrid Approach to Optimization", pages = "174--183", ISBN = "1-55860-370-0", editor = "Larry J. Eshelman", booktitle = "Proceedings of the 6th International Conference on Genetic Algorithms", publisher = "Morgan Kaufmann Publishers", address = "San Francisco", year = "1995" } @article{Ferreira_Zerovnik_93, author = "A.G. Ferreira and J. Zerovnik", title = "Bounding the probability of success of stochastic methods for global optimization", journal = "Computers \& Mathematics with Applications", pages ="1-8", year = "1993" } @article{Shonkwiler_VanVleck_94, title = "Parallel speed-up of Monte Carlo Methods for Global Optimization", author = "R. Shonkwiler and E. Van Vleck", journal = "Journal of Complexity", volume = "10", pages ="64-95", year = "1994" } @article{Verhoeven_Aarts_95, title = "Parallel Local Search", author = "M.G.A. Verhoeven and E.H.L. Aarts", journal = "Journal of Heuristics", volume = "1", pages = "43-65", year = "1995" } @Article{Pirlot_96, title = "General local search methods", author = "M. Pirlot", journal = "European Journal of Operational Research", volume = "92", number = "3", pages = "493--511", year = "1996", publisher = "Elsevier Science BV, Amsterdam" } @mastersthesis{Hofmann_thesis_93, author = "R. Hofmann", title = "Examinations on the Algebra of Genetic Algorithms", school = "Technische Universit{\"a}t M{\"u}nchen, Institut f{\"u}r Informatik", year = "1993" } %% Peter Merz's publications %% First version, September 14, 1998 %% Updated, May, 2001. @mastersthesis{merz96, author = "Peter Merz", title = "Genetische Algorithmen f{\"u}r kombinatorische Optimierungsprobleme", school = "Department of Computer Science, University of Siegen, Germany", year = "1996" } @InProceedings{fspm96:icec, author = "B. Freisleben and P. Merz", title = "{A Genetic Local Search Algorithm for Solving Symmetric and Asymmetric Traveling Salesman Problems}", booktitle = "Proceedings of the 1996 IEEE International Conference on Evolutionary Computation", editor = "T. B{\"a}ck and H. Kitano and Z. Michalewicz", publisher = "{IEEE Press}", address = "Piscataway, NJ, USA", year = "1996", pages = "616--621" } @InProceedings{fspm96:ppsn, author = "B. Freisleben and P. Merz", title = "{New Genetic Local Search Operators for the Traveling Salesman Problem}", booktitle = "Proceedings of the 4th International Conference on Parallel Problem Solving from Nature - PPSN IV", editor = "H.-M. Voigt and W. Ebeling and I. Rechenberg and H.-P. Schwefel", series = "Lecture Notes in Computer Science", volume = 1141, publisher = "Springer", address = "Berlin, Germany", pages = "890--900", year = "1996" } @InProceedings{pmfs97:icec, author = "P. Merz and B. Freisleben", title = "{Genetic Local Search for the TSP: New Results}", booktitle = "Proceedings of the 1997 IEEE International Conference on Evolutionary Computation", publisher = "{IEEE Press}", address = "Piscataway, NJ, USA", editor = "T. B{\"a}ck and Z. Michalewicz and X. Yao", pages = "159--164", year = "1997" } @InProceedings{pmfs97:icga, author = "P. Merz and B. Freisleben", title = "{A Genetic Local Search Approach to the Quadratic Assignment Problem}", booktitle = "Proceedings of the 7th International Conference on Genetic Algorithms", editor = "T. B{\"a}ck", publisher = "Morgan Kaufmann", address = "San Francisco, CA, USA", pages = "465--472", year = "1997" } @InProceedings{Merz_Freisleben_BQP_99, author = "P. Merz and B. Freisleben", title = "{Genetic Algorithms for Binary Quadratic Programming}", booktitle = "GECCO-1999: Proceedings of the Genetic and Evolutionary Computation Conference", editor = "W. Banzhaf and Jason Daida and Agoston E. Eiben and Max H. Garzon and Vasant Honavar and Mark Jakiela and Robert E. Smith", publisher = "{Morgan Kauffman}", address = "San Francisco, CA", year = "1999", pages = "417--424" } @InProceedings{pmfs98:icec, author = "P. Merz and B. Freisleben", title = "{On the Effectiveness of Evolutionary Search in High--Dimensional $NK$-Landscapes}", booktitle = "Proceedings of the 1998 IEEE International Conference on Evolutionary Computation", editor = "D. Fogel", publisher = "{IEEE Press}", address = "Piscataway, NJ, USA", pages = "741--745", year = "1998" } @InProceedings{pmfs98:ppsn, author = "P. Merz and B. Freisleben", title = "{Memetic Algorithms and the Fitness Landscape of the Graph Bi-Partitioning Problem}", booktitle = "Proceedings of the 5th International Conference on Parallel Problem Solving from Nature - PPSN V", editor = "A.-E. Eiben and T. B{\"a}ck and M. Schoenauer and H.-P. Schwefel", series = "Lecture Notes in Computer Science", volume = 1498, publisher = "Springer", address = "Berlin, Germany", year = "1998", pages = "765--774" } @article{pmfs2000:tec, author = "P. Merz and B. Freisleben", title = "{Fitness Landscape Analysis and Memetic Algorithms for the Quadratic Assignment Problem}", journal = "IEEE Transactions on Evolutionary Computation", volume = 4, number = 4, pages = "337--352", year = "2000" } @TechReport{pmfs2000:joh, author = "P. Merz and B. Freisleben", title = "{Greedy and Local Search Heuristics for Unconstrained Binary Quadratic Programming}", institution = "Department of Electrical Engineering and Computer Science, University of Siegen", address = "Germany", note = "Accepted for publication in {\em Journal of Heuristics}", year = "2000" } @TechReport{pmkk01:tr, author = "Peter Merz and Kengo Katayama", title = "{A Hybrid Evolutionary Local Search Approach for the Unconstrained Binary Quadratic Programming Problem}", institution = "Department of Computer Science, University of T{\"u}bingen", address = "Germany", year = "2001" } @PhdThesis{pm2000:phd, author = "P. Merz", title = "{Memetic Algorithms for Combinatorial Optimization Problems: Fitness Landscapes and Effective Search Strategies}", school = "Department of Electrical Engineering and Computer Science, University of Siegen", address = "Germany", year = "2000" } @InProceedings{iceo96, author = "H. Bersini and M. Dorigo and S. Langerman and G. Seront and L. Gambardella", title = "{Results of the First International Contest on Evolutionary Optimisation (1st ICEO)}", booktitle = "Proceedings of the 1996 IEEE International Conference on Evolutionary Computation, Nagoya, Japan", publisher = "{IEEE Press}", address = "Piscataway, NJ, USA", year = "1996", pages = "611--615" } @InProceedings{Moscato92, title = "{A Memetic Approach for the Traveling Salesman Problem Implementation of a Computational Ecology for Combinatorial Optimization on Message-Passing Systems}", author = "P. Moscato and M. G. Norman", editor = "M. Valero and E. Onate and M. Jane and J. L. Larriba and B. Suarez", booktitle = "Parallel Computing and Transputer Applications", publisher = "IOS Press", address = "Amsterdam", pages = "177--186", year = "1992" } @TechReport{Moscato89a, title = "A Competitive and Cooperative Approach to Complex Combinatorial Search", author = "M.G. Norman and P. Moscato", number = "Caltech Concurrent Computation Program, Report. 790", institution = "California Institute of Technology", address = "Pasadena, California, USA", note = "expanded version published at the Proceedings of the 20th Informatics and Operations Research Meeting, Buenos Aires (20th JAIIO), Aug. 1991, pp. 3.15--3.29", year = "1989" } @TechReport{Moscato89, title = "{On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts: Towards Memetic Algorithms}", author = "P. Moscato", number = "Caltech Concurrent Computation Program, Report. 826", institution = "California Institute of Technology", address = "Pasadena, California, USA", year = "1989" } % ``Go with the winners'' algorithms @InProceedings{Aldous_Vazirani_94, author ="D. Aldous and U. Vazirani", title ="{``Go with the winners'' algorithms}", booktitle ="Proceedings of the 35th Annual Symposium on Foundations of Computer Science", year ="1994", publisher ="IEEE", address = "Los Alamitos, CA", pages = "492--501" } @InProceedings{Peinado_Lengauer_97b, author ="M. Peinado and T. Lengauer", title ="{Parallel ``go with the winners algorithms'' in the LogP Model}", booktitle ="Proceedings of the 11th International Parallel Processing Symposium", year ="1997", editor ="IEEE Computer Society Press", publisher ="Los Alamitos, California", pages = "656--664" } @InProceedings{Muehlenbein89genetic, author ="H. M{\"u}hlenbein", title ="{Parallel Genetic Algorithms, Population Genetics and Combinatorial Optimization}", booktitle ="Proceedings of the Third International Conference on Genetic Algorithms", year ="1989", editor ="Schaffer", publisher ="Morgan Kaufmann", keywords ="genetic algorithms", ref ="genetic", pages = "416--421" } @Article{Muehlenbein88combi, author ="H. M{\"u}hlenbein and M. Gorges-Schleuter and O. Kr{\"a}mer", title ="{Evolution Algorithms in Combinatorial Optimization}", journal ="Parallel Computing", year ="1988", ref ="combi", volume ="7", pages ="65--88" } @InProceedings{Muhlenbein91a:ga, author ="H. M{\"u}hlenbein", title ="{Evolution in Time and Space -- The Parallel Genetic Algorithm}", booktitle ="Foundations of Genetic Algorithms", pages ="316--337", editor ="Gregory J.E. Rawlins", publisher ="Morgan Kaufmann Publishers", address ="San Mateo, CA, USA", year ="1991" } @InCollection{Mu91, author = "H. M{\"u}hlenbein", title = "{Parallel Genetic Algorithms in Combinatorial Optimization}", booktitle = "Computer Science and Operations Research", editor = "O. Balci, R. Sharda and S. Zenios", year = "1992", publisher = "Pergamon Press, New York", pages = "441--456" } @InProceedings{GorgesSchleuter91, author = "M. Gorges-Schleuter", title = "{Explicit Parallelism of Genetic Algorithms through Population Structures}", editor = {H.-P. Schwefel and R. M{\"a}nner}, booktitle = {Parallel Problem Solving from Nature, 1st Workshop, PPSN I, Dortmund, FRG, October 1-3, 1990, Proceedings}, publisher = {Springer-Verlag}, address = "Berlin, Germany", pages = "150--159", series = {Lecture Notes in Computer Science}, volume = {496}, year = {1991}, isbn = {3-540-54148-9}, bibsource = {DBLP, http://dblp.uni-trier.de} } @InProceedings{GorgesSchleuter89, author = "M. Gorges-Schleuter", title = "{ASPARAGOS}: An Asynchronous Parallel Genetic Optimization Strategy", booktitle = "Proceedings of the Third International Conference on Genetic Algorithms", editor = "J. David Schaffer", pages = "422--427", publisher = "Morgan Kaufmann Publishers", year = "1989" } @InProceedings{GorgesSchleuter97, author = "M. Gorges-Schleuter", title = "Asparagos96 and the Traveling Salesman Problem", booktitle = "Proceedings of the 1997 IEEE International Conference on Evolutionary Computation, Indianapolis, USA", editor = {Th. B\"ack and Z. Michalewicz and X. Yao}, publisher = "{IEEE Press}", address = "Piscataway, NJ, USA", pages = "171--174", year = "1997" } @InProceedings{Jog89, key ="ICGA", booktitle ="Proceedings of the Third International Conference on Genetic Algorithms", year ="1989", publisher ="Morgan Kaufman", author ="P. Jog and J.Y. Suh and D. Van Gucht", title ="{The Effects of Population Size, Heuristic Crossover and Local Improvement on a Genetic Algorithm for the Travelling Salesman Problem}", pages ="110--115" } @InProceedings{Liepins87, editor = "Grefenstette, J.J.", booktitle = "Proceedings of the Second International Conference on Genetic Algorithms and their Applications", address = "Cambridge, MA", month = jul, year = "1987", publisher = "Lawrence Erlbaum Associates", author = "G. E. Liepins and M. R. Hilliard", title = "{Greedy Genetics}", pages = "90--99" } @InProceedings{Suh87, editor = "Grefenstette, J.J.", booktitle = "Proceedings of the Second International Conference on Genetic Algorithms and their Applications", address = "Cambridge, MA", month = jul, year = "1987", publisher = "Lawrence Erlbaum Associates", author = "J.Y. Suh and D. Van Gucht", title = "{Incorporating Heuristic Information into Genetic Search}", pages = "100--107" } @InProceedings{Eshelman91, booktitle = "Proceedings of the 4th International Conference on Genetic Algorithms", year = "1991", publisher = "Morgan Kaufmann", author = "L. J. Eshelman and J. D. Schaffer", title = "{Preventing Premature Convergence in Genetic Algorithms by Preventing Incest}", pages = "115--122" } @InProceedings{Manderick91, key = "ICGA", booktitle = "Proceedings of the 4th International Conference on Genetic Algorithms", year = "1991", publisher = "Morgan Kaufmann", author = "B. Manderick and M. de Weger and P. Spiessens", title = "{The Genetic Algorithm and the Structure of the Fitness Landscape}", pages = "143--150" } @InProceedings{Braun91, author = "H. Braun", title = "{On Solving Traveling Salesman Problems by Genetic Algorithms}", editor = "H.-P. Schwefel and R. M{\"{a}}nner", volume = "496", series = "Lecture Notes in Computer Science", pages = "129--133", booktitle = "Parallel Problem Solving from Nature - Proceedings of 1st Workshop, PPSN I", year = "1991", publisher = "Springer", address = "Berlin, Germany" } @InProceedings{Dzubera94, author = "J. Dzubera and D. Whitley", title = "{Advanced Correlation Analysis of Operators for the Traveling Salesman Problem}", editor = "H.-P. Schwefel and R. M{\"{a}}nner", volume = "866", series = "Lecture Notes in Computer Science", pages = "68--77", booktitle = "Parallel Problem Solving from Nature - Proceedings of the Third Workshop, PPSN III", year = "1994", publisher = "Springer-Verlag, Berlin, Germany", address = "Dortmund, Germany" } @InProceedings{Ulder91, author = "N. L. J. Ulder and E. H. L. Aarts and H. -J. Bandelt and P. J. M. van Laarhoven and E. Pesch", title = "{Genetic Local Search Algorithms for the Traveling Salesman Problem}", editor = "H. -P. Schwefel and R. M{\"{a}}nner", volume = "496", series = "Lecture Notes in Computer Science", pages = "109--116", booktitle = "Parallel Problem Solving from Nature - Proceedings of 1st Workshop, PPSN I", year = "1991", publisher = "Springer", address = "Berlin, Germany" } @InProceedings{Mathias92, author = "K. Mathias and D. Whitley", title = "{Genetic operators, the Fitness Landscape and the Traveling Salesman Problem}", editor = "R. M{\"{a}}nner and B. Manderick", pages = "219--228", booktitle = "Parallel Problem Solving from Nature - Proceedings of 2nd Workshop, PPSN II", year = "1992", publisher = "Elsevier Science Publishers" } @InProceedings{Grefenstette87, author = "J.J. Grefenstette", title = "{Incorporating Problem Specific Knowledge into Genetic Algorithms}", editor = "L. Davis", pages = "42--60", booktitle = "Genetic Algorithms and Simulated Annealing", year = "1987", publisher = "Morgan Kaufmann Publishers", series = "Research Notes in Artificial Intelligence" } @InProceedings{Yamada96, author = "T. Yamada and R. Nakano", title = "{Scheduling by Genetic Local Search with Multi-Step Crossover}", booktitle = "Proceedings of the 4th Conference on Parallel Problem Solving from Nature - PPSN IV", editor = "Hans-Michael Voigt and Werner Ebeling and Ingo Rechenberg and Hans-Paul Schwefel", series = "Lecture Notes in Computer Science", volume = 1141, publisher = "Springer", pages = "960--969", year = "1996" } @InCollection{Eshelman91a, editor = "G. J. E. Rawlings", booktitle = "Foundations of Genetic Algorithms", publisher = "Morgan Kaufmann", year = "1991", author = "L.J. Eshelman", title = "{The CHC Adaptive Search Algorithm: How to Have Safe Search When Engaging in Nontraditional Genetic Recombination}", pages = "265--283" } @InProceedings{Ronald95:icec, author = "Simon Ronald", title = "{Finding Multiple Solutions with an Evolutionary Algorithm}", booktitle = "Proceedings of the 1995 IEEE International Conference on Evolutionary Computation", publisher = "{IEEE Press}", pages = "641--646", year = "1995" } @InProceedings{Ronald97:icec, author = "Simon Ronald", title = "{Distance Functions for Order--Based Encodings}", booktitle = "Proceedings of the 1997 IEEE International Conference on Evolutionary Computation", editor = "T. B{\"a}ck and Z. Michalewicz and X. Yao", publisher = "{IEEE Press}", address = "Piscataway, NJ, USA", pages = "49--54", year = "1997" } @InCollection{Eshelman97:foga, title = "{Convergence Controlled Variation}", author = "Larry Eshelman and K. Mathias and J. D. Schaffer", booktitle = "Foundations of Genetic Algorithms 4", year = "1997", editor = "Richard K. Belew and Michael D. Vose", publisher = "Morgan Kaufman", pages = "203--224" } @phdthesis{Niehaus_96, author = "William J. Niehaus", title = "Design of Maximum-Cardinality and Maximum-Weight Clique Heuristics with Applications", organisation = "School of Computer Science", school = "Carnegie Mellon University", type = "Ph.D. Thesis, CMU-CS-96-127", address = "Pittsburgh, PA, USA", year = "1996", note = "Niehaus and Balas presented a talk at the INFORMS conference in 1996 entitled: Genetic Algorithms for maximum clique. The abstract of the talk is available at: http://www.informs.org/Conf/WA96/TALKS/MC29.3.html" } @InProceedings{Radcliffe_formal_memetics, author = "N.J. Radcliffe and P.D. Surry", title = "{Formal Memetic Algorithms}", booktitle = "Evolutionary Computing: AISB Workshop", editor = "T. Fogarty", pages = "1--16", series = "Lecture Notes in Computer Science", year = "1994", publisher = "Springer-Verlag, Berlin", volume = "865", abstract = "A formal, representation-independent form of a memetic algorithm---a genetic algorithm incorporating local search---is introduced. A generalised form of $N$-point crossover is defined together with representation-independent patching and hill-climbing operators. The resulting formal algorithm is then constructed and tested empirically on the travelling sales-rep problem. Whereas the genetic algorithms tested were unable to make good progress on the problems studied, the memetic algorithms performed very well." } @InProceedings{Radcliffe_performance_prediction, author = "N.J. Radcliffe and P.D. Surry", title = "{Fitness Variance of Formae and Performance Prediction}", booktitle = "Proceedings of the Third Workshop on Foundations of Genetic Algorithms", pages = "51--72", editor = "L.D. Whitley and M.D. Vose", publisher = "Morgan Kaufmann", address = "San Francisco", year = "1994", abstract = " Representation is widely recognised as a key determinant of performance in evolutionary computation. The development of families of representation-independent operators allows the formulation of formal representation-independent evolutionary algorithms. These formal algorithms can be instantiated for particular search problems by selecting a suitable representation. The performance of different representations, in the context of any given formal representation-independent algorithm, can then be measured. Simple analyses suggest that fitness variance of formae (generalised schemata) for the chosen representation might act as a performance predictor for evolutionary algorithms. This hypothesis is tested and supported through studies of four different representations for the travelling sales-rep problem (TSP) in the context of both formal representation-independent genetic algorithms and corresponding memetic algorithms." } @book{Gen_Cheng_book, title = "Genetic Algorithms and Engineering Design", author = "M. Gen and R. Cheng", series = "Wiley Series in Engineering Design and Automation", publisher = "John Wiley \& Sons (Sd)", year = "1997", ISBN = "0471127418" } @article{Cheng_Gen_97, title = "Parallel machine scheduling problems using memetic algorithms", author = "R.W. Cheng and M. Gen", journal = "Computers \& Industrial Engineering", volume = "33", number = "3--4", pages = "761--764", year = "1997", document_type = "Article", language = "English", cited_references = "5", abstract = "In this paper, we investigate how to apply the hybrid genetic algorithms (the memetic algorithms) to solve the parallel machine scheduling problem. There are two essential issues to be dealt with for all kinds of parallel machine scheduling problems: job partition among machines and job sequence within each machine. The basic idea of the proposed method is that (a) use the genetic algorithms to evolve the job partition and then (b) apply a local optimizer to adjust the job permutation to push each chromosome climb to his local optima. Preliminary computational experiments demonstrate that the hybrid genetic algorithm outperforms the genetic algorithms and the conventional heuristics.", author_keywords = "parallel machine scheduling, hybrid genetic algorithms, memetic algorithms", addresses = " Cheng RW, Ashikaga Inst Technol, Dept Ind \& Syst Engn, Ashikaga 326, Japan. Ashikaga Inst Technol, Dept Ind \& Syst Engn, Ashikaga 326, Japan.", publisher = " PERGAMON-ELSEVIER SCIENCE LTD, OXFORD", ids_number = " YM357", issn = " 0360-8352" } @misc{ division-evolutionary, author = "Fukunaga Division", title = "Evolutionary Programming", url = "citeseer.nj.nec.com/53947.html" } @misc{ fukunaga-towards, author = "Alex Fukunaga", title = "Towards a Self-Configuring Optimization System for Spacecraft Design", url = "citeseer.nj.nec.com/57407.html" } @InProceedings{Mendes_et_al_99, author = "A.S. Mendes and F.M. Muller and P.M. {Fran\c{c}a} and P. Moscato", title = "Comparing Meta-Heuristic Approaches for Parallel Machine Scheduling Problems with Sequence-dependent setup times", booktitle = "Proceedings of the 15th International Conference on CAD/CAM Robotics \& Factories of the Future, Aguas de Lindoia, Brasil", volume = "1", pages = "1-6", year ="1999", publisher = "Technological Center for Informatics Foundation", address = "Campinas, SP, Brazil", abstract = "The aim of this paper is to compare the performance of two meta-heuristic methods proposed for solving the identical parallel machine scheduling problem with sequence dependent setup times. The first algorithm is a tabu search based heuristic and the second a memetic approach, which combines population-based methods with local search procedures. As benchmarks for small-sized instances we use optimal solutions provided by a dichotomous search. For larger instances the comparisons rely on the best known solutions." } @InProceedings{Franca_Mendes_Moscato_99, author = "P.M. {Fran\c{c}a} and A.S. Mendes and P. Moscato", title = "Memetic algorithms to minimize tardiness on a single machine with sequence-dependent setup times", booktitle = "Proceedings of the 5th International Conference of the Decision Sciences Institute, Athens, Greece", pages = "1708--1710", year ="1999", publisher = "Decision Sciences Institute", address = "Atlanta, GA, USA" } @misc{ brumby00genetic, author = "S. Brumby and N. Harvey and S. Perkins and R. Porter and J. Szymanski and J. Theiler and J. Bloch", title = "A genetic algorithm for combining new and existing image processing tools for multispectral imagery", text = "Brumby, S.P., N.R. Harvey, S. Perkins, R.B. Porter, J.J. Szymanski, J. Theiler, and J.J. Bloch, A genetic algorithm for combining new and existing image processing tools for multispectral imagery, to appear in proceedings of SPIE 4049 (2000).", year = "2000", url = "citeseer.nj.nec.com/brumby00genetic.html" } % set partitioning @InCollection{Levine96, title = "A parallel genetic algorithm for the set partitioning problem", author = "D. Levine", booktitle = "Meta-Heuristics: Theory \& Applications", editor = "I.H. Osman and J.P. Kelly", pages = "23--35", publisher = "Kluwer Academic Publishers", address = "Boston, MA, USA", year = "1996" } % set covering @article{Beasley_Chu_96, title ="A genetic algorithm for the set covering problem", author = "J. Beasley and P.C. Chu", journal = "European Journal of Operational Research", volume = "94", number ="2", pages = "393--404", year = "1996", abstract = "In this paper we present a genetic algorithm-based heuristic for solving the set partitioning problem (SPP). The SPP is an important combinatorial optimisation problem used by many airlines as a mathematical model for flight crew scheduling. A key feature of the SPP is that it is a highly constrained problem, all constraints being equalities. New genetic algorithm (GA) components: separate fitness and unfitness scores, adaptive mutation, matching selection and ranking replacement, are introduced to enable a GA to effectively handle such constraints. These components are generalisable to any GA for constrained problems. We present a steady-state GA in conjunction with a specialised heuristic improvement operator for solving the SPP. The performance of our algorithm is evaluated on a large set of real-world problems. Computational results show that the genetic algorithm-based heuristic is capable of producing high-quality solutions." } % multidimensional knapsack @article{Beasley_Chu_98, title = "A genetic algorithm for the multidimensional knapsack problem", author = "J. Beasley and P.C. Chu", journal = "Journal of Heuristics", volume = "4", pages = "63--86", year = "1998", abstract = "In this paper we present a heuristic based upon genetic algorithms for the multidimensional knapsack problem. A heuristic operator which utilises problem-specific knowledge is incorporated into the standard genetic algorithm approach. Computational results show that the genetic algorithm heuristic is capable of obtaining high-quality solutions for problems of various characteristics, whilst requiring only a modest amount of computational effort. Computational results also show that the genetic algorithm heuristic gives superior quality solutions to a number of other heuristics." } % generalized assignment @article{Beasley_Chu_97, title = "A genetic algorithm for the generalised assignment problem", author = "P.C. Chu and J. Beasley", journal = "Computers \& Operations Research", volume = "24", pages = "17--23", year = "1997", abstract = "In this paper we present a genetic algorithm (GA)-based heuristic for solving the generalised assignment problem. The generalised assignment problem is the problem of finding the minimum cost assignment of $n$ jobs to $m$ agents such that each job is assigned to exactly one agent, subject to an agent's capacity. In addition to the standard GA procedures, our GA heuristic incorporates a problem-specific coding of a solution structure, a fitness-unfitness pair evaluation function and a local improvement procedure. The performance of our algorithm is evaluated on 84 standard test problems of various sizes ranging from 75 to 4,000 decision variables. Computational results show that the genetic algorithm heuristic is able to find optimal and near optimal solutions that are on average less than 0.01% from optimality. The performance of our heuristic also compares favourably to all other existing heuristic algorithms in terms of solution quality." } % Scheduling @article{Costa_NHL, author = "D. Costa", title = "An evolutionary tabu search algorithm and the {NHL} scheduling Problem", journal = "INFOR", volume = "33", number= "3", year = "1995", pages = "161--178" } % Graph Coloring References @InProceedings{Hogg_Williams_93, author = "Tad Hogg and Colin P. Williams", title = "Solving the Really Hard Problems with Cooperative Search", booktitle = "Proc. of AAAI93", pages = "231--236", publisher = "AAAI Press", address = "Menlo Park, CA", year = "1993", abstract = "We present and experimentally evaluate the hypothesis that cooperative parallel search is well suited for hard graph coloring problems near a previously identified transition between under- and overconstrained instances. We find that simple cooperative methods can often solve such problems faster than the same number of independent agents. " } @article{Costa_coloring, author = "D. Costa and N. Dubuis and A. Hertz", title = "Embedding of a sequential procedure within an evolutionary algorithm for coloring problems in graphs", journal = "Journal of Heuristics", volume = "1", number= "1", year = "1995", pages = "105-128" } @article{Fleurent_Ferland_96, title = "Genetic and hybrid algorithms for graph coloring", author = "C. Fleurent and J.A. Ferland", journal = "Annals of Operations Research", volume = "63", pages = "437--461", year = "1997", abstract ="Some genetic algorithms are considered for the graph coloring problem. As is the case for other combinatorial optimization problems, pure genetic algorithms are outperformed by neighborhood search heuristic procedures such as tabu search. Nevertheless, we examine the performance of several hybrid schemes that can obtain solutions of excellent quality. For some graphs, we illustrate that genetic operators can fulfill long-term strategic functions for a tabu search implementation that is chiefly founded on short-term memory strategies." } @InProceedings{Dorne_Hao_98, AUTHOR = {R. Dorne and J.K. Hao}, TITLE = {A New Genetic Local Search Algorithm for Graph Coloring}, editor = {Eiben, A.E. and B\"ack, Th. and Schoenauer, M. and Schwefel, H.-P.}, booktitle = {Parallel Problem Solving From Nature V}, year = {1998}, series = {Lecture Notes in Computer Science}, volume = {1498}, publisher = {Springer-Verlag}, address = {Berlin}, PAGES = {745-754}, } @article{galinierhao98, author = "P. Galinier and J.K. Hao", title = "Hybrid evolutionary algorithms for graph coloring", journal = "Journal of {C}ombinatorial {O}ptimization", volume = "3", number ="4", pages = "379--397", year = "1999" } @article{Bui_Moon_96, title = "Genetic algorithm and graph partitioning", author = "T.N. Bui and B.R. Moon", journal = "IEEE Transactions on Computers", volume = "45", number = "7", pages = "841--855", year = "1996", abstract = "Hybrid genetic algorithms (GAs) for the graph partitioning problem are described. The algorithms include a fast local improvement heuristic. One of the novel features of these algorithms is the schema preprocessing phase that improves GAs' space searching capability, which in turn improves the performance of GAs. Experimental tests on graph problems with published solutions showed that the new genetic algorithms performed comparable to or better than the multistart Kernighan-Lin algorithm and the simulated annealing algorithm. Analyses of some special classes of graphs are also provided showing the usefulness of schema preprocessing and supporting the experimental results." } @article{Bui_Moon_98, title ="{GRCA}: A hybrid genetic algorithm for circuit ratio-cut partitioning", author ="T.N. Bui and B.R. Moon", journal = "IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems", volume ="17", number = "3", pages ="193--204", year = "1998", abstract = "A genetic algorithm for partitioning a hypergraph into two disjoint graphs of minimum ratio cut is presented. As the Fiduccia-Mattheyses graph partitioning heuristic turns out to be not effective when used in the context of a hybrid genetic algorithm, we propose a modification of the Fiduccia-Mattheyses heuristic for more effective and faster space search by introducing a number of novel features. We also provide a preprocessing heuristic for genetic encoding designed solely for hypergraphs which helps genetic algorithms exploit clustering information of input graphs. Supporting combinatorial arguments for the new preprocessing heuristic are also provided. Experimental results on industrial benchmarks circuits showed visible improvement over recently published algorithms with a lower growth rate of running time." } % Bin Packing @article{Reeves_96, title = "Hybrid genetic algorithms for bin-packing and related problems", author = "C. Reeves", journal = "Annals of Operations Research", volume = "63", pages = "371--396", year = "1996", abstract = "The genetic algorithm (GA) paradigm has attracted considerable attention as a promising heuristic approach for solving optimization problems. Much of the development has related to problems of optimizing functions of continuous variables, but recently there have been several applications to problems of a combinatorial nature. What is often found is that GAs have fairly poor performance for combinatorial problems if implemented in a naive way, and most reported work has involved somewhat ad hoc adjustments to the basic method. In this paper, we will describe a general approach which promises good performance for a fairly extensive class of problems by hybridizing the GA with existing simple heuristics. The procedure will be illustrated mainly in relation to the problem of bin-packing, but it could be extended to other problems such as graph partitioning, parallel-machine scheduling and generalized assignment. The method is further extended by using problem size reduction hybrids. Some results of numerical experiments will be presented which attempt to identify those circumstances in which these heuristics will perform well relative to exact methods. Finally, we discuss some general issues involving hybridization: in particular, we raise the possibility of blending GAs with orthodox mathematical programming procedures." } % maximum independent set @article{Aggarwal_Orlin_Tai_97, title = "Optimized Crossover for the Independent Set Problem", author = "C.C. Aggarwal and J.B. Orlin and R.P. Tai", journal = "Operations Research", volume = "45", pages ="226--234", number = "2", year ="1997", abstract = "We propose a knowledge-based crossover mechanism for genetic algorithms that exploits the structure of the solution rather than its coding. More generally, we suggest broad guidelines for constructing the knowledge-based crossover mechanisms. This technique uses an optimized crossover mechanism, in which the one of the two children is constructed in such a way as to have the best objective function value from the feasible set of children, while the other is constructed so as to maintain the diversity of the search space. We implement our approach on a classical combinatorial problem, called the independent set problem, The resulting genetic algorithm dominates all other genetic algorithms for the problem and yields one of the best heuristics for the independent set problem in terms of robustness and time performance. The primary purpose of this paper is to demonstrate the power of knowledge based mechanisms in genetic algorithms." } @article{Hifi_97, title = "A genetic algorithm-based heuristic for solving the weighted maximum independent set and some equivalent problems", author = "M. Hifi", journal = "Journal of the Operational Research Society", volume = "48", number = "6", pages = "612--622", year = "1997", abstract = "In this paper we present a genetic algorithm-based heuristic especially for the weighted maximum independent set problem (IS). The proposed approach treats also some equivalent combinatorial optimization problems. We introduce several modifications to the basic genetic algorithm, by (i) using a crossover called two-fusion operator which creates two new different children and (ii) replacing the mutation operator by the heuristic-feasibility operator tailored specifically for the weighted independent set. The performance of our algorithm was evaluated on several randomly generated problem instances for the weighted independent set and on some instances of the DIMACS Workshop for the particular case: the unweighted maximum clique problem. Computational results show that the proposed approach is able to produce high-quality solutions within reasonable computational times. This algorithm is easily parallelizable and this is one of its important features." } @article{Sakamoto_Liu_Shimamoto_97, title = "A genetic approach for maximum independent set problems", author = "A. Sakamoto and X.Z. Liu and T. Shimamoto", journal = "{IEICE} Transactions on Fundamentals of Electronics Communications and Computer Sciences", volume = "E80A", number = "3", pages = "551--556", year = "1997", abstract = "Genetic algorithms have been shown to be very useful in a variety of search and optimization problems. In this paper we present a genetic algorithm for maximum independent set problem. We adopt a permutation encoding with a greedy de coding to solve the problem. The DIMACS benchmark graphs are used to test our algorithm. For most graphs solutions found by our algorithm are optimal, and there are also a few exceptions that solutions found by the algorithm are almost as large as maximum clique sizes. We also compare our algorithm with a hybrid genetic algorithm, called GMCA, and one of the best existing maximum clique algorithms, called CBH. The experimental mental results show that our algorithm outperformed two of the best approaches by GMCA and CBH in final solutions." } % (nonlinear) integer programming @article{Taguchi_Yokota_Gen_98, title = "Reliability optimal design problem with interval coefficients using Hybrid Genetic Algorithms", author = "T. Taguchi and T. Yokota and M. Gen", journal = "Computers \& Industrial Engineering", volume = "35", number ="1--2", pages = "373--376", year = "1998", abstract = "In this paper, we formulate an optimal design of system reliability problem as nonlinear integer programming (NIP) problem with interval coefficients! transform it into single objective NIP problem without interval coefficients, and solve it directly keeping the nonlinearity of the objective function based on Hybrid Genetic Algorithms (HGAs). Also, we demonstrate the efficiency of this method with Optimal Selection and Allocation problem of a System Reliability." } % chapters of the book New Ideas in optimization % 23 Feb. 1999 @book{NewMethods_99, title = "New Ideas in Optimization", author = "D. Corne and M. Dorigo and F. Glover", year = "1999", publisher = "McGraw-Hill", address = "Maidenhead, Berkshire, England, UK" } @InCollection{Moscato_NewMethods_99, title = "Memetic Algorithms: A short introduction", author = "P. Moscato", booktitle = "New Ideas in Optimization", editor = "D. Corne and M. Dorigo and F. Glover", year = "1999", pages = "219--234", publisher = "McGraw-Hill", address = "Maidenhead, Berkshire, England, UK" } @TECHREPORT{voudouris97, AUTHOR = "C. Voudouris", TITLE = "Guided Local Search-an illustrative example in function optimisation ", INSTITUTION = "University of Essex", YEAR = "1998", } @CONFERENCE{voudouris96, author = {C. Voudouris and E. Tsang}, title = {Partial constraint satisfaction problems and guided local search}, booktitle = {Proceedings of 2nd International Conference on Practical Application on constaint technology}, year = {1996}, pages = {337-356}, month = {April}, annote = {London} } @PHDTHESIS{voudouris97b, AUTHOR = "C. Voudouris", TITLE = "Guided Local search for combinatorial optimization problems", SCHOOL = "Department of computer science, University of Essex", YEAR = "1997", type = "PhD Thesis", address = "Colchester,UK", month = "July" } @InCollection{Holstein_Moscato_NewMethods_99, title = "Memetic Algorithms using Guided Local Search: A case study", author = "D. Holstein and P. Moscato", booktitle = "New Ideas in Optimization", editor = "D. Corne and M. Dorigo and F. Glover", year = "1999", pages = "235--244", publisher = "McGraw-Hill", address = "Maidenhead, Berkshire, England, UK" } @InCollection{Coll_Duran_Moscato_NewMethods_99, title = "On worst-case and comparative analysis as design principles for efficient recombination operators: A graph coloring case study", author = "P.E. Coll and G.A. Dur\'an and P. Moscato", booktitle = "New Ideas in Optimization", editor = "D. Corne and M. Dorigo and F. Glover", year = "1999", pages = "279--294", publisher = "McGraw-Hill", address = "Maidenhead, Berkshire, England, UK" } @Misc{Moscatopage, author = {P. Moscato}, title = {Memetic Algorithms' home page}, howpublished = {http://www.densis.fee.unicamp.br/~moscato/memetic_home.html}, year = {2003}, note = {Page Created in February 1996} } @Manual{Naher96, title ={The LEDA User Manual Version R 3.3.c} , author = {S. Naher and C. Uhrig}, year = {1996} } @PhdThesis{Pahud98, author = {M. Pahud}, title = {Une Method de Prediction de Performance pour les Programmes Paralleles Irreguliers}, school = {Swiss Federal Institute of Technology}, year = {1998}, OPTmonth = {December}, OPTnote = {number 1911}, } @InCollection{Merz_Freisleben_NewMethods_99, title = "Fitness Landscapes and Memetic Algorithm Design", author = "P. Merz and B. Freisleben", booktitle = "New Ideas in Optimization", editor = "D. Corne and M. Dorigo and F. Glover", year = "1999", pages = "245--260", publisher = "McGraw-Hill", address = "Maidenhead, Berkshire, England, UK" } @InCollection{Berretta_Moscato_NewMethods_99, title = "The Number Partitioning Problem: An open challenge for Evolutionary Computation~?", author = "R. Berretta and P. Moscato", booktitle = "New Ideas in Optimization", editor = "D. Corne and M. Dorigo and F. Glover", year = "1999", pages = "261--278", publisher = "McGraw-Hill", address = "Maidenhead, Berkshire, England, UK" } @InProceedings{cacic98, author = "N. Krasnogor and P.A. Mocciola and D.A. Pelta and G. Ruiz and W.M. Russo", title = "A Runnable Functional Memetic Algorithm Framework", booktitle = "Proceedings of the Congreso Argentino de Ciencias de la Computacion, Vol. I", pages = "525--536", year = "1998", address = "Universidad Nacional del Comahue, Argentina" } % Evolution of Cooperation @article{Axelrod_Hamilton_81, title = "The Evolution of Cooperation", author = "R. Axelrod and W.D. Hamilton", journal = "Science", volume = "211", number = "4489", pages = "1390--1396", year = "1981" } @article{Hofstadter_83, title = "Computer Tournaments of the Prisoners-Dilemma Suggest How Cooperation Evolves", author = "D.R. Hofstadter", journal = "Scientific American", volume = "248", number = "5", pages = "16--23", year = "1983" } @article{Nowak_Sigmund_98, title = "Evolution of indirect reciprocity by image scoring", author = "M.A. Nowak and K. Sigmund", journal = "Nature", volume = "393", number = "6685", pages = "573--577", year = "1998" } @BOOK{85ribeiro, AUTHOR = "I. Foster", TITLE = "Designing and building parallel programs:Concepts and tools for parallel software", PUBLISHER = "Addison-Wesley", YEAR = "1995", } @BOOK{121ribeiro, AUTHOR = "V. Kumar, A. Grama, A. Gupta and G. Karypis", TITLE = "Introduction to parallel computing design and analysis of parallel algorithms", PUBLISHER = "Benjaming/Cummings", YEAR = "1994", } @BOOK{144ribeiro, AUTHOR = "H.S. Morse", TITLE = "Practical parallel computing", PUBLISHER = "AP Professional", YEAR = "1994", } @article{Nakamaru_Nogami_Iwasa_98, title = "Score-dependent fertility model for the evolution of cooperation in a lattice", author = "M. Nakamaru and H. Nogami and Y. Iwasa", journal = "Journal of Theoretical Biology", volume ="194", number ="1", pages = "101--124", year ="1998", Abstract = "The evolution of cooperation is studied in a lattice-structured population, in which each individual plays the iterated Prisoner's Dilemma game with its neighbors. The population includes Tit-for-Tat (TFT, a cooperative strategy) and All Defect (AD, a selfish strategy) distributed over the lattice points. An individual dies randomly, and the vacant site is filled immediately by a copy of one of the neighbors in which the probability of colonization success by a particular neighbor is proportional to its score accumulated in the game. This ``score-dependent fertility model'' (or fertility model) behaves very differently from score-dependent viability model (viability model) studied in a previous paper. The model on a one-dimensional lattice is analysed by invasion probability analysis, pair-edge method mean-held approximation, pair approximation, and computer simulation. Results are: (1) TFT players come to form tight clusters. When the probability of iteration w is large, initially rare TFT can invade and spread in a population, dominated by AD, unlike in the complete mixing model. The condition for the increase of TFT is accurately predicted by all the techniques except mean-field approximation; (2) fertility model is much more favorable for the spread of TFT than the corresponding viability model, because spiteful killing of neighbors is favored in the viability model but not in the fertility model; (3) eight lattice games on two-dimensional lattice with different assumptions are examined. Cooperation and defects can coexist stable in the models of deterministic state change but not in the models of stochastic state change." } @article{Nakamaru_Matsuda_Iwasa_98a, title = "The evolution of social interaction in lattice models", author ="M. Nakamaru and H. Matsuda and Y. Iwasa", journal = "Sociological Theory and Methods", volume ="12", number ="2", pages = "149--162", year ="1998", abstract = "The rationality of human behavior seems unable to explain the altruism and spite which gives the player a short-term cost. Recent study of evolutionary game theory succeed to explain the condition for these social interaction to appear, based on the dynamics of different behaviors in the population. The critical importance of the spatial structure as been revealed- if players interact locally, the society to evolve is very different from if they interact randomly over the whole population. In this article, we review the studies on the evolution of social interaction in lattice structured models (or cellular automata models). The analysis of lattice models have been restricted to direct computer simulations. Here we apply various mathematical analyses, including birth-and-death processes, pair-approximation, and the pair-edge method." } @article{Grim_97, title = "The undecidability of the spatialized prisoner's dilemma", author = "P. Grim", journal = "Theory and Decision", volume = "42", number = "1", pages = "53--80", year = "1997", abstract = "In the spatialized Prisoner's Dilemma, players compete against their immediate neighbors and adopt a neighbor's strategy should it prove locally superior. Fields of strategies evolve in the manner of cellular automata (Nowak and May, 1993; Mar and St. Denis, 1993a,b; Grim 1995, 1996). Often a question arises as to what the eventual outcome of an initial spatial configuration of strategies will be: Will a single strategy prove triumphant in the sense of progressively conquering more and more territory without opposition, or will an equilibrium of some small number of strategies emerge? Here it is shown, for finite configurations of Prisoner's Dilemma strategies embedded in a given infinite background, that such questions are formally undecidable: there is no algorithm or effective procedure which, given a specification of a finite configuration, will in all cases tell us whether that configuration will or will not result in progressive conquest by a single strategy when embedded in the given field. The proof introduces undecidability into decision theory in three steps: by (1) outlining a class of abstract machines with familiar undecidability results, by (2) modelling these machines within a particular family of cellular automata, carrying over undecidability results for these, and finally by (3) showing that spatial configurations of Prisoner's Dilemma strategies will take the form of such cellular automata." } % The following set of references have been cited in % % "Memetic Algorithms for molecular conformation and other % optimization problems", by P. Moscato, % appeared in the Newsletter No. 20, May-August, 1998, of the % International Union of Crystallography, % Newsletter of the Comission for Powder Diffraction. % % available from the Newsletter web site at % % http://www.dl.ac.uk/SRS/XRD/IUCR/Newsletters/no20summer1998/ @article{Moscato_93, author = "P. Moscato", title = "{An Introduction to Population Approaches for Optimization and Hierarchical Objective Functions: The Role of Tabu Search}", journal = "Annals of Operations Research", volume = "41", number= "1-4", year = "1993", pages = " 85-121", abstract = "Population approaches suitable for global combinatorial optimization are discussed in this paper. They are composed of a number of distinguishable individuals called ``agents'', each one using a particular optimization strategy. Periods of independent search follow phases on which the population is restarted from new configurations. Due to its intrinsic parallelism and the asynchronicity of the method, it is particularly suitable for parallel computers. Results on two test problems are presented in this paper. The individual search optimization strategies for each agent have been chosen having the basic characteristics of Tabu Search. This has been done in order to avoid mixing the hypothesized properties of these population approaches with those of more elaborate Tabu Search strategies, but remarking on its main characteristics. A set of four test problem ``landscapes'' is discussed and their use to improve and benchmark the results by using Tabu Search as the individual optimization strategy within a population heuristic is suggested and explored. The application of Tabu Search to new problem areas, like molecular biology, is also investigated." } @article{Glover_95, title="Scatter Search And Star-Paths - Beyond The Genetic Metaphor", author="F. Glover", journal="{OR} Spektrum", volume = "17", number = "(2-3)", pages = "125--137", year = "1995", Abstract = "Scatter search and genetic algorithms have originated from somewhat different traditions and perspectives, yet exhibit features that are strongly complementary. Links between the approaches have increased in recent years as variants of genetic algorithms have been introduced that embody themes in closer harmony with those of scatter search. Some researchers are now beginning to take advantage of these connections by identifying additional ways to incorporate elements of scatter search into genetic algorithm approaches. There remain aspects of the scatter approach that have not been exploited in conjunction with genetic algorithms, yet that provide ways to achieve goals that are basic to the genetic algorithm design. Part of the gap in implementing hybrids of these procedures may derive from relying too literally on the genetic metaphor, which in its narrower interpretation does not readily accommodate the strategic elements underlying scatter search. The theme of this paper is to show there are benefits to be gained by going beyond a perspective constrained too tightly by the connotations of the term ``genetic''. We show that the scatter search framework directly leads to processes for combining solutions that exhibit special properties for exploiting combinatorial optimization problems. In the setting of zero-one integer programming, we identify a mapping that gives new ways to create combined solutions, producing constructions called star-paths for exploring the zero-one solution space. Star-path trajectories have the special property of lying within regions assured to include optimal solutions. They also can be exploited in association with both cutting plane and extreme point solution approaches. These outcomes motivate a deeper look into current conceptions of appropriate ways to combine solutions, and disclose there are more powerful methods to derive information from these combinations than those traditionally applied." } @article{Huber_94, Title="Structural Optimization of Vapor-Pressure Correlations Using Simulated Annealing And Threshold Accepting - Application To R134A", Author ="M.L. Huber", Journal = "Computers \& Chemical Engineering", Volume = "18", Number = "(10)", Pages = "929--932", Year = "Oct. 1994", Abstract = "This paper reports the use of two methods, simulated annealing (SA) and threshold accepting (TA), to determine a set of optimal terms (the structure) of the vapor pressure correlation for the R134a. The SA algorithm with the Lundy and Mees annealing schedule, and the TA algorithm with the Aarts and VanLaarhoven schedule gave the best performance, based on minimal computational time for a given performance. SA and TA appear to be versatile, powerful and computationally simple methods for determining the structure of empirical correlations of thermophysical property data.", } @article{Glover_94, Title="Genetic Algorithms And Scatter Search - Unsuspected Potentials", Author = "F. Glover", Journal = "Statistics And Computing", Volume = "4", Number = "(2)", Pages = "131--140", Year = "1994", Abstract = "We provide a tutorial survey of connections between genetic algorithms and scatter search that have useful implications for developing new methods for optimization problems. The links between these approaches are rooted in principles underlying mathematical relaxations, which became inherited and extended by scatter search. Hybrid methods incorporating elements of genetic algorithms and scatter search are beginning to be explored in the literature, and we demonstrate that the opportunity exists to develop more advanced procedures that make fuller use of scatter search strategies and their recent extensions." } @article{Landree_97, Title="Multi-solution memetic algorithm approach to surface structure determination using direct methods", Author = "E. Landree and C. Collazo-Davila and L.D. Marks", Journal = "Acta Crystallographica Section B - Structural Science", Volume = "53", Pages = "916--922", Year = "1997", Abstract = "We show that it is possible to use a multi-solution genetic algorithm search method utilizing direct methods to solve surface structures from surface diffraction data. We suggest that the method is generally applicable and able to replace random searches of the solution space." } @article{Miller_96, Title="A genetic algorithm for the {\em ab initio} phasing of icosahedral viruses", Author = "S.T. Miller and J.M. Hogle and D.J. Filman", Journal = "Acta Crystallographica Section D - Biological Crystallography", Volume = "52", Pages = "235--251", Year ="1996", Abstract = "Genetic algorithms have been investigated as computational tools for the de novo phasing of low-resolution X-ray diffraction data from crystals of icosahedral viruses. Without advance knowledge of the shape of the virus and only approximate knowledge of its size, the virus can be modeled as the symmetry expansion of a short list of nearly tetrahedrally arranged lattice points which coarsely, but uniformly, sample the icosahedrally unique volume. The number of lattice points depends on an estimate of the non-redundant information content at the working resolution limit. This parameterization permits a simple matrix formulation of the model evaluation calculation, resulting in a highly efficient survey of the space of possible models. Initially, one bit per parameter is sufficient, since the assignment of ones and zeros to the lattice points yields a physically reasonable low-resolution image of the virus. The best candidate solutions identified by the survey are refined to relax the constraints imposed by the coarseness of the modeling, and then trials whose intensity-based statistics are comparatively good in all resolution ranges are chosen. This yields an acceptable starting point for symmetry-based direct phase extension about half the time. Improving efficiency by incorporating the selection criterion directly into the genetic algorithm's fitness function is discussed." } @article{Choi_98, Title="X-ray reflectivity analysis incorporated with genetic algorithm to analyze the Y- to X type transition in CdA LB film", Author ="J.W. Choi and K.S. Cho and H.W. Rhee and W.H. Lee and H.S. Lee", Journal = "Bulletin of the Korean Chemical Society", Volume = "19", Number ="5", Pages ="549--553", Year = "1998", Abstract = " The structure and layer distribution of cadmium arachidate Langmuir-Blodgett film were analyzed by the small angle X-ray reflectivity measurements using synchrotron radiation. Y- to X type transition was occurred during the 39th passage of deposition of cadmium arachidate. Based on the measurement of the consumed area of the monolayer, it was determined that about 27.5 layer was deposited. Using the synchrotron X-ray, the: reflectivity profile of cadmium arachidate LB Nm over the wide range of grazing angle was obtained. The X-ray reflectivity profile was analyzed using the recursion formula. By fitting the location and dispersion of the subsidiary maxima between the Bragg peaks of the measured reflectivity profile with that of the calculated reflectivity profile, the average thickness and the distribution of layer thickness were evaluated. The genetic algorithm was adopted to the fitting of reflectivity profile to evaluate the optimum value of the number distribution of layer. Based on the morphology measurement with an atomic force microscopy (AFM), the domain structure and mean roughness of LB films were obtained. The mean roughness value calculated based on the number of layer distribution obtained from the measurement by AFM is consistent with that obtained from X-ray reflectivity analysis.", } @article{Trinkunas_97, Title="Model for the excitation dynamics in the light-harvesting complex II from higher plants", Author = "G. Trinkunas and J.P. Connelly and M.G. Muller and L. Valkunas and A. R. Holzwarth", Journal = "Journal of Physical Chemistry B", Volume = "101", Number = "37", Pages = "7313--7320", Year = "1997", Abstract = "A model for the spectral characteristics, the transition dipole moment orientations, and the energy transfer properties of chlorophyll (Chl) a and b molecules in the light-harvesting complex (LHC) II is proposed on the basis of the results from femtosecond transient measurements and other spectroscopic data. The model uses the structural data (Kuhlbrandt; et al. Nature 1994, 367, 614) and is obtained using a genetic algorithm search of the large parameter space. Forster resonance transfer has been assumed as the mechanism of energy transfer. The spectral and orientational assignments of all twelve Chl molecules of a LHC II monomer are proposed. In the best fit model two of the seven Chl molecules that are proximal to the central luteins are Chl b. In contrast to prior assumptions, the basic feature of the model consists of an intermediately strong coupling (V < 100 cm(-1)) between the Chl a and b molecules in close pairs and the absence of substantial excitonic coupling between Chls a, thus indicating an overall limited influence of excitonic effects on spectra and kinetics. A theoretical estimation of exciton effects supports these model assumptions. Over most of the difference absorption spectrum good agreement between experimental and theoretical kinetics has been obtained. Energy transfer times in the symmetric LHC II trimer range from 90 fs to 5.1 ps. For the monomeric complexes only the longest lifetime is significantly affected and predicted to be just slightly longer (6.6 ps). The predicted transition dipole moment orientations result in weak coupling between the LHC II monomers. Several possible routes to improve both the data fitting and the reliability of the predictions in the future are discussed.", KeyWordsPlus=" TRANSIENT ABSORPTION-SPECTROSCOPY, ULTRAFAST ENERGY-TRANSFER, A/B PROTEIN COMPL EX, LHC-II, PHOTOSYSTEM-II, PHOTOSYNTHETIC SYSTEMS, CHLOROPHYLL-A, ELECTRON CRYSTALLOGRAPHY , CHLOROPLAST MEMBRANES, EXCITON MIGRATION" } @article{Zwick_96, Title="Global optimization studies on the 1-D phase problem", Author ="M. Zwick and B. Lovell and J. Marsh", Journal="International Journal of General Systems", Volume ="25", Number ="1", Pages ="47--59", Year ="1996", Abstract = "The Genetic Algorithm (GA) and Simulated Annealing (SA), two techniques for global optimization, were applied to a reduced (simplified) form of the phase problem (RPP) in computational crystallography. Results were compared with those of ''enhanced pair flipping'' (EPF), a more elaborate problem-specific algorithm incorporating local and global searches. Not surprisingly, EPF did better than the GA or SA approaches, but the existence of GA and SA techniques more advanced than those used in this study suggest that these techniques still hold promise for phase problem applications. The RPP is, furthermore, an excellent test problem for such global optimization methods.", AuthorKeywords =" phase problem, computational crystallography, global optimization, Genetic Algo rithm, simulated annealing" } @Book{45, author = {D.E. Goldberg}, title = {Genetics algorithms in search, optimization, and machine learning}, publisher = {Addison-Wesley Publishing Company}, year = {1989} } @article{Jones_97, Title="Development and validation of a genetic algorithm for flexible docking", Author ="G. Jones and P. Willett and R.C. Glen and A.R. Leach and R. Taylor", Journal ="Journal of Molecular Biology", Volume ="267", Number ="3", Pages ="727--748", Year = "1997", Abstract = "Prediction of small molecule binding modes to macromolecules of known three-dimensional structure is a problem of paramount importance in rational drug design (the ''docking'' problem). We report the development and validation of the program GOLD (Genetic Optimisation for Ligand Docking). GOLD is an automated Ligand docking program that uses a genetic algorithm to explore the full range of ligand conformational flexibility with partial flexibility of the protein, and satisfies the fundamental requirement that the ligand must displace loosely bound water on binding. Numerous enhancements and modifications have been applied to the original technique resulting in a substantial increase in the reliability and the applicability of the algorithm. The advanced algorithm has been tested on a dataset of 100 complexes extracted from the Brookhaven Protein DataBank. When used to dock the ligand back into the binding site, GOLD achieved a 71% success rate in identifying the experimental binding mode.", AuthorKeywords="docking problem, genetic algorithm, molecular recognition, prot ein ligand docking", KeyWordsPlus =" REFINED CRYSTAL-STRUCTURE, X-RAY CRYSTALLOGRAPHY, ESCHERICHIA-COLI, DIHYDROFOLATE-REDUCTASE, 3-DIMENSIONAL STRUCTURE, CONFORMATIONAL-CHANGES, MOLEC ULAR RECOGNITION, ANGSTROM RESOLUTION, BINDING PROTEIN, BETA-LACTAMASE" } @ARTICLE{alex1, author = {Alexouda G. and K. Paparrizos}, title = {A Genetic Algorithm Approach to the Product Line Design Problem using the Seller's Return Criterion: An Extensive Comparative Computational Study}, journal = {European Journal of Operational Research}, year = {2001}, volume = {34}, number = {1}, pages = {167-180} } @ARTICLE{Alex3, author = {Alexouda G. and K. Paparrizos}, title = {A Genetic Algorithm Approach to the Buyers' Welfare Problem of Product Line Design: A comparative computational study}, journal = {Yugoslav Journal of Operations Research}, year = {1999}, volume = {2}, pages = {223-233}} @misc{ szymanski02feature, author = "J. Szymanski and S. Brumby and P. Pope and D. Eads and D. Esch-Mosher and M. Galassi and N. Harvey and H. McCulloch and S. Perkins and R. Porter and J. Theiler and A. Young and J. Bloch and N. David", title = "Feature Extraction from Multiple Data Sources using Genetic Programming", text = "J.P. Szymanski, S.P. Brumby, P. Pope, D.R. Eads, D. Esch-Mosher, M. Galassi, N.R. Harvey, H.D.W. McCulloch, S.J. Perkins, R. Porter, J. Theiler, A.C. Young, J.J. Bloch, and N. David, Feature Extraction from Multiple Data Sources using Genetic Programming, Proc. SPIE 4725, 2002.", year = "2002", url = "citeseer.nj.nec.com/szymanski02feature.html" } @article{Doll_96, Title="Global optimization in {LEED} structure determination using genetic algorithms", Author ="R. Doll and M.A. VanHove", Journal ="Surface Science", Volume ="355", Number ="1-3", Pages ="L393--L398", Year ="1996", Abstract = "By application of search algorithms, low energy electron diffraction (LEED) structure determination is now capable of solving relatively complicated systems. However, since LEED is a diffraction technique, the danger remains in identifying an incorrect structure because a local rather than a global minimum in the R-factor hypersurface was found. Recently it has been suggested that simulated annealing could be employed to circumvent this potential problem. In this Letter, using the Ir(110)-(1 x 2) missing row structure as an example, we demonstrate that genetic algorithms can also be used for a full structural analysis. Our results indicate that a rough global search using a genetic algorithm, followed by structural refinement using conventional steepest descent methods, should yield the correct structure within a typically tractable timescale.", AuthorKeywords ="electron-solid diffraction, iridium, low energy electron diffr action (LEED), low index single crystal surfaces, surface structure", KeyWordsPlus = "ENERGY-ELECTRON-DIFFRACTION, SURFACE-STRUCTURE DETERMINATION, TENSOR LEED, CRYSTALLOGRAPHY." } @misc{ brumby02evolving, author = "S. Brumby and J. Theiler and J. Bloch and N. Harvey and S. Perkins and J. Szymanski and A. Young", title = "Evolving land cover classification algorithms for multi-spectral and multi-temporal imagery", text = "S. P. Brumby, J. Theiler, J. J. Bloch, N. R. Harvey, S. Perkins, J. J. Szymanski, and A. C. Young. Evolving land cover classification algorithms for multi-spectral and multi-temporal imagery, Proc. SPIE 4480, 120-129 (2002).", year = "2002", url = "citeseer.nj.nec.com/brumby02evolving.html" } @article{MacKay_95, Title="Generalized Crystallography", Author ="A.L. MacKay", Journal ="THEOCHEM-Journal of Molecular Structure", Volume ="336", Number ="2--3", Pages ="293--303", Year ="1995", Abstract = "The paradigm of X-ray crystal structure analysis has provided the structures of some 200000 molecular, ionic and metallic substances. The disadvantage of the direct methods used in restoring the phases of the scattered waves is the necessary assumption that all unit cells in the crystals are the same. With the appearance of electron microscopy and scanning tunnelling microscopy, which do not lose the phases on recording, the imaging of more general objects has become possible. A sketch of some of the components which might comprise a generalisation of classical crystallography is attempted. In particular, it is suggested that a biological approach to inorganic:systems might provide new insight. The construction of an 'inorganic gene' as a computing device is proposed.", AuthorKeywords =" CRYSTALLOGRAPHY, GENETIC ALGORITHM, INORGANIC GENE, VORONOI" } @article{Chacon_98, Title="Low-resolution structures of proteins in solution retrieved from X-ray scattering with a genetic algorithm", Author ="P. Chacon and F. Moran and J.F. Diaz and E. Pantos and J.M. Andreu", Journal ="Biophysical Journal", Volume ="74", Number ="6", Pages ="2760--2775", Year = "1998", Abstract = "Small-angle x-ray solution scattering (SAXS) is analyzed with a new method to retrieve convergent model structures that fit the scattering profiles. An arbitrary hexagonal packing of several hundred beads containing the problem object is defined. Instead of attempting to compute the Debye formula for all of the possible mass distributions, a genetic algorithm is employed that efficiently searches the configurational space and evolves best-fit bead models. Models from different runs of the algorithm have similar or identical structures. The modeling resolution is increased by reducing the bead radius together with the search space in successive cycles of refinement. The method has been tested with protein SAXS (0.001 < S < 0.06 Angstrom(-1)) calculated from x-ray crystal structures, adding noise to the profiles. The models obtained closely approach the volumes and radii of gyration of the known structures, and faithfully reproduce the dimensions and shape of each of them. This includes finding the active site cavity of lysozyme, the bilobed structure of gamma-crystallin, two domains connected by a stalk in beta b2-crystallin, and the horseshoe shape of pancreatic ribonuclease inhibitor. The low-resolution solution structure of lysozyme has been directly modeled from its experimental SAXS profile (0.003 < S < 0.03 Angstrom(-1)). The model describes lysozyme size and shape to the resolution of the measurement. The method may be applied to other proteins, to the analysis of domain movements, to the comparison of solution and crystal structures, as well as to large macromolecular assemblies.", KeyWordsPlus =" SMALL-ANGLE SCATTERING, DIRECT SHAPE DETERMINATION, CURVE-FITTING PROCEDURE, NEUTRON-SCATTERING, SYNCHROTRON-RADIATION, MOLECULAR RECOGNITION, SECONDARY STR UCTURE, CRYSTAL-STRUCTURE, MYOSIN HEAD, MACROMOLECULES" } @article{Shankland_98, Title="Structure solution of Ibuprofen from powder diffraction data by the application of a genetic algorithm combined with prior conformational analysis", author ="K. Shankland and W.I.F. David and T. Csoka and L. McBride", journal ="International Journal of Pharmaceutics", volume ="165", number ="1", pages ="117--126", year ="1998", Abstract = "The crystal structure of Ibuprofen has been solved from synchrotron X-ray powder diffraction data using a genetic algorithm based model building method. The performance of the algorithm is enhanced if additional prior chemical information is incorporated in the form of hard limits on the values that can be assumed by flexible torsion angles within the molecule.", AuthorKeywords = "Ibuprofen, crystal structure solution, X-ray powder diffracti on, genetic algorithm", KeyWordsPlus = "STRUCTURE-FACTOR AMPLITUDES" } @article{Cui_98, Title="Protein folding simulation with genetic algorithm and supersecondary structure constraints", Author ="Y. Cui and R.S. Chen and W.H. Wong", Journal ="Proteins-Structure Function And Genetics", Volume ="31", Number ="3", Pages ="247--257", Year ="1998", Abstract = "We describe an algorithm to compute native structures of proteins from their primary sequences. The novel aspects of this method are: 1) The hydrophobic potential was set to be proportional to the nonpolar solvent accessible surface. To make computation feasible, we developed a new algorithm to compute the solvent accessible surface areas rapidly. 2) The supersecondary structures of each protein were predicted and used as restraints during the conformation searching processes, This algorithm was applied to five proteins. The overall fold of these proteins can be computed from their sequences, with deviations from crystal structures of 1.48-4.48 Angstrom for C-alpha atoms.", AuthorKeywords = " protein structure prediction, supersecondary structure, genetic algorithm, solv ent accessible surface area, hydrophobic potential", KeyWordsPlus ="ACCESSIBLE SURFACE-AREA, ANALYTICAL MOLECULAR-SURFACE, NEAR-NATI VE FOLDS, STRUCTURE PREDICTION, GLOBULAR-PROTEINS, X-RAY, VOLUME, ENERGY, PACKI NG, SOLVENT" } @article{Lorber_98, Title="Flexible ligand docking using conformational ensembles", Author ="D.M. Lorber and B.K. Shoichet", Journal ="Protein Science", Volume ="7", Number ="4", Pages ="938--950", Year ="1998", Abstract = "Molecular docking algorithms suggest possible structures for molecular complexes. They are used to model biological function and to discover potential ligands. A present challenge for docking algorithms is the treatment of molecular flexibility. Here, the rigid body program, DOCK, is modified to allow it to rapidly fit multiple conformations of ligands. Conformations of a given molecule are pre-calculated in the same frame of reference, so that each conformer shares a common rigid fragment with all other conformations. The ligand conformers are then docked together, as an ensemble, into a receptor binding site. This takes advantage of the redundancy present in differing conformers of the same molecule. The algorithm was tested using three organic ligand protein systems and two protein-protein systems. Both the bound and unbound conformations of the receptors were used. The ligand ensemble method found conformations that resembled those determined in X-ray crystal structures (RMS values typically less than 1.5 Angstrom). To test the method's usefulness for inhibitor discovery, multi-compound and multi-conformer databases were screened for compounds known to bind to dihydrofolate reductase and compounds known to bind to thymidylate synthase. In both cases, known inhibitors and substrates were identified in conformations resembling those observed experimentally. The ligand ensemble method was 100-fold faster than docking a single conformation at a time and was able to screen a database of over 34 million conformations from 117,000 molecules in one to four CPU days on a workstation.", AuthorKeywords ="conformation, flexibility, molecular docking, structure-based drug design", KeyWordsPlus="AUTOMATED DOCKING, DIHYDROFOLATE-REDUCTASE, MOLECULAR DOCKING, BE TA-LACTAMASE, DRUG DESIGN, 3-DIMENSIONAL STRUCTURE, LACTATE-DEHYDROGENASE, CRYS TAL-STRUCTURES, GENETIC ALGORITHM, ESCHERICHIA-COLI" } @article{Michaelian_98, Title="Evolving few-ion clusters of {Na} and {Cl}", Author ="K. Michaelian", Journal ="American Journal of Physics", Volume ="66", Number ="3", Pages ="231--240", Year ="Mar. 1998", Abstract = "The ground state configuration of a macroscopic quantity of Na and Cl ions is the well-known crystalline, face-centered cubic structure (table salt). However, when the number of ions is reduced to a handful, geometrically quite different and interesting ground state structures occur. Such configurations are realized in the early stages of crystal growth and are important in a growing number of physical applications. This article describes the application of a genetic algorithm to the difficult problem of the determination of the lowest-energy geometrical configurations of few-ion (less than or equal to 12) clusters of Na and Cl. The binding energy and the frequencies of vibration determined for these structures are compared to experimental data and to published results of other calculations. The advantages and limitations of the genetic algorithm as a tool for cluster physics are discussed.", KeyWordsPlus="LENNARD-JONES CLUSTERS, GENETIC ALGORITHMS, SEARCH, DYNAMICS, ENE RGY, MICROCLUSTERS, OPTIMIZATION, SIMPLICITY, MOLECULES, SURFACES", } article{Poirrette_97, Title="Comparison of protein surfaces using a genetic algorithm", Author ="A.R. Poirrette and P.J Artymiuk D.W. Rice and P. Willett", Journal ="Journal of Computer-Aided Molecular Design", Volume ="11", Number ="6", Pages ="557--569", Year = "Nov. 1997", Abstract = "A genetic algorithm (GA) is described which is used to compare the solvent-accessible surfaces of two proteins or fragments of proteins, represented by a dot surface calculated using the Connolly algorithm. The GA is used to move one surface relative to the other to locate the most similar surface region between the two. The matching process is enhanced by the use of the surface normals and shape terms provided by the Connolly program and also by a simple hydrogen-bonding descriptor and an additional shape descriptor. The algorithm has been tested in applications ranging from the comparison of small surface patches to the comparison of whole protein surfaces, and it has performed correctly in all cases. Examples of the matches are given and a quantitative analysis of the quality of the matches is performed. A number of possible future enhancements to the program are described which would allow the GA to be used for more complex surface comparisons.", AuthorKeywords="protein structure, molecular surfaces, structure comparison, bi nding sites, evolutionary computation", } @article{Bayley_98, Title="GENFOLD: A genetic algorithm for folding protein structures using {NMR} restraints", Author = "M.J. Bayley and G. Jones and P. Willett and M.P. Williamson", Journal = "Protein Science", Volume = "7", Number = "2", Pages = "491--499", Year = "1998", Abstract = "We report the development and validation of the program GENFOLD, a genetic algorithm that calculates protein structures using restraints obtained from NMR, such as distances derived from nuclear Overhauser effects, and dihedral angles derived from coupling constants. The program has been tested on three proteins: the POU domain (a small three-helix DNA-binding protein), bovine pancreatic trypsin inhibitor (BPTI), and the starch-binding domain from Aspergillus niger glucoamylase I, a 108-residue beta-sheet protein. Structures were calculated for each protein using published NMR restraints. In addition, structures were calculated for BPTI using artificial restraints generated from a high-resolution crystal structure. In all cases the fittest calculated structures were close to the target structure, and could be refined to structures indistinguishable from the target structures by means of a low-temperature simulated annealing refinement. The effectiveness of the program is similar to that of distance geometry and simulated annealing methods, and it is capable of using a very wide range of restraints as input. It can thus be readily extended to the calculation of structures of large proteins, for which few NOE restraints may be available." } @article{deSouza_98, Title="Automation of the analysis of {Mossbauer} spectra", Author = "P.A. de Souza and R. Garg and V.K. Garg", Journal ="Hyperfine Interactions", Volume ="112", Number ="1--4", Pages ="275--278", Year ="1998", Abstract = "In the present report we propose the automation of least square fitting of Mossbauer spectra, the identification of the substance, its crystal structure and the access to the references with the help of a genetic algorithm, Fuzzy logic, and the artificial neural network associated with a databank of Mossbauer parameters and references. This system could be useful for specialists and non-specialists, in industry as well as in research laboratories.", KeyWordsPlus = " ARTIFICIAL NEURAL-NETWORK, IDENTIFICATION", } @article{White_98, Title="A study of genetic algorithm approaches to global geometry optimization of aromatic hydrocarbon microclusters", Author ="R.P. White and J.A. Niesse and H.R. Mayne", Journal ="Journal of Chemical Physics", Volume ="108", Number ="5", Pages ="2208--2218", Year ="1998", Abstract = "We have carried out potential energy minimization calculations on benzene, naphthalene, and anthracene clusters using model potential energy functions. The primary purpose was to examine several techniques which use concepts from the field of genetic algorithms (GA). In particular, we compared the ``traditional GA'' in which the variables of the problem are coded into binary and genetic operations performed on these, and recent methods which use real-valued variables. Our primary technique, the ``space-fixed modified GA'' (SFMGA), also uses a conjugate gradient descent on the geometries generated by the GA. Our results show the convergence to the global minimum is greatly improved by the use of the descent minimization. In fact, it appears unlikely that the traditional GA's are useful for any but the very simplest clusters. We have also compared the SFMGA with simulated annealing (SA) and Wales and Doye's recent basin-hopping (BH) technique. We find our method to be superior to SA, and comparable to BH.", KeyWordsPlus = "LENNARD-JONES CLUSTERS, SMALL BENZENE CLUSTERS, SCHRODINGER-EQU ATION, CRYSTAL-STRUCTURES, ATOMIC CLUSTERS, MONTE-CARLO, MINIMUM, PREDICTION, S EARCHES" } @article{Kariuki_97, Title="The application of a genetic algorithm for solving crystal structures from powder diffraction data", Author ="B.M. Kariuki and H. Serrano-Gonzalez and R.L. Johnston and K.D.M. Harris", Journal ="Chemical Physics Letters", Volume ="280", Number ="3-4", Pages ="189--195", Year ="1997", Abstract = "We report the successful application of a genetic algorithm to tackle crystal structure solution from powder diffraction data in the case of a previously unknown structure - ortho-thymotic acid. In the structure solution calculation, the structural fragment was subjected to combined translation and rotation within the unit cell, together with variation of selected intramolecular degrees of freedom under the control of a genetic algorithm, in which a population of trial structures is allowed to evolve subject to well-defined procedures for mating, mutation and natural selection. Importantly, the genetic algorithm approach adopts the `direct-space' philosophy for structure solution, and implicitly avoids the problematic step of extracting the intensities of individual reflections from the powder diffraction data. The structure solution was found efficiently in the genetic algorithm calculation, and was then used as the initial structural model in Rietveld refinement calculations. The work reported in this Letter paves the way for the future application of the genetic algorithm approach to a much wider array of structural problems.", KeyWordsPlus = "MONTE-CARLO METHODS, X-RAY" } @article{Apostolakis_98, Title="Docking small ligands in flexible binding sites", Author ="J. Apostolakis and A. Pluckthun and A. Caflisch", Journal ="Journal of Computational Chemistry", Volume ="19", Number ="1", Pages ="21--37", Year ="Jan. 15, 1998", Abstract = "A novel procedure for docking ligands in a flexible binding site is presented. It relies on conjugate gradient minimization, during which nonbonded interactions are gradually switched on. Short Monte Carlo minimization runs are performed on the most promising candidates. Solvation is implicitly taken into account in the evaluation of structures with a continuum model. It is shown that the method is very accurate and can model induced fit in the ligand and the binding site. The docking procedure has been successfully applied to three systems. The first two are the binding of progesterone and 5 beta-androstane-3, 17-dione to the antigen binding fragment of a steroid binding antibody. A comparison of the crystal structures of the free and the two complexed forms reveals that any attempt to model binding must take protein rearrangements into account. Furthermore, the two ligands bind in two different orientations, posing an additional challenge. The third test case is the docking of N-alpha-(2-naphthyl-sulfonyl-glycyl)-D-para-amidino-phenyl-alanyl-piperidine (NAPAP) to human alpha-thrombin. In contrast to steroids, NAPAP is a very flexible ligand, and no information of its conformation in the binding site is used. All docking calculations are started from X-ray conformations of proteins with the uncomplexed binding site. For all three systems the best minima in terms of free energy have a root mean square deviation from the X-ray structure smaller than 1.5 Angstrom for the ligand atoms.", AuthorKeywords =" antisteroid antibody, progesterone, thrombin, NAPAP, flexible docking, MSNI, MCM, finite-difference Poisson-Boltzmann technique", KeyWordsPlus = "MONTE-CARLO-MINIMIZATION, COPY SIMULTANEOUS SEARCH, THROMBIN IN HIBITORS, 3-DIMENSIONAL STRUCTURE, MOLECULAR RECOGNITION, ELECTROSTATIC ENERGY, AUTOMATED DOCKING, GENETIC ALGORITHM, CONTINUUM MODEL, ALPHA-THROMBIN" } @article{Ikeda_97, Title="A new method of alloy design using a genetic algorithm and molecular dynamics simulation and its application to nickel-based superalloys", Author ="Y. Ikeda", Journal ="Materials Transactions Jim", Volume ="38", Number ="9", Pages ="771--779", Year ="1997", Abstract = "A new method of allay design was proposed using a genetic algorithm and molecular dynamics simulations. In this method, evaluations of physical quantities using molecular dynamics simulations and an efficient global search using a genetic algorithm allow optimization of an equilibrium composition for a multi-component alloy satisfying a given design rule. The ahoy design method was used to design nickel-based superalloys in the elemental systems simulating those of TMS-63 and CMSX-2. The obtained atom fractions in the gamma phase and gamma' phase, and atom fractions in the Ni and Al sublattices of the gamma' phase were compared with the experimental values. The comparisons showed that the global features of TMS-63 and CMSX-2 were reproduced well. Furthermore negative lattice misfits were of about 1% and positive elastic misfits for c(11) and c(12) were of about 10% for both alloys. Finally sources of the inaccuracies for the obtained atom fractions and possible improvements for the design method were discussed." } @article{Fleischer_97, Title="D-QSAR analysis and molecular modeling investigations of piritrexim and analogous", Author ="R. Fleischer and M. Wiese and R. Troschutz and M. Zink", Journal ="Journal of Molecular Modeling", Volume ="3", Number ="8", Pages ="338--346", Year ="1997", Abstract = "Quantitative structure-activity, relationships for piritrexim and analogues acting as inhibitors of tumour cell growth have been derived. First the Free-Wilson-method was used on a homologous training set of night derivatives. The selection of variables important for the biological activity of the compounds was carried out with different multivariate methods as multiple linear regression, the partial least squares method and a genetic algorithm. The derivation of three-dimensional structure activity relationships started with a systematic conformational analysis of all compounds. For the conformations having minimal energy and being in agreement with the crystal structure of piritrexim charges were calculated with the AM1 hamiltonian. For the superimposition of the derivatives two methods were used: maximal similarity of the common substructure or of the molecular fields. A Comparative Molecular Field Analysis with steric and electrostastic fields identified regions important for the activity of the studied compounds independent of the chosen alignment and also correctly predicted the activity of two nonhomologous compounds." } @article{Shankland_97, Title="Crystal structure determination from powder diffraction data by the application of a genetic algorithm", Author ="K. Shankland and W.I.F. David and T. Csoka", Journal ="Zeitschrift {Fur} Kristallographie", Volume ="212", Number = "8", Pages = "550--552", Year ="1997", Abstract = "A genetic algorithm (GA) based method for solving crystal structures directly from powder diffraction data has been developed. The method is based around fitting the diffraction data generated film trial structures against the measured diffraction data and has the ability to handle flexible molecules and multiple fragments. It is computationally highly efficient and takes full advantage of the implicit parallelism of the GA. The method is illustrated with the solutions of three crystal structures of varying complexity." } @article{Sahara_97, Title="A Monte Carlo simulation describing melting transition of Si-type structure in the condensed phase with BCC lattice model including many-body interactions", author ="R. Sahara and H. Mizuseki and K. Ohno and S. Uda and T. Fukuda and Y. Kawazoe", journal ="Science Reports of The Research Institutes Tohoku University Series A -Physics Chemistry And Metallurgy", volume ="43", number ="1", pages ="23--28", year =" Mar. 1997", Abstract = "A new lattice model is proposed for Si crystallization from molten state, which is based on Monte Carlo (MC) simulation. In this model, each atom is allowed to move only on BCC lattice sites, and the potential energy of atom depends on the configuration in the Ist nearest neighbors. With the parameter that only the atoms constructing tetrahedron have lower energy than others, the Ist-order phase transition between diamond and random structures is observed, including a hysteresis behavior. On the other hand, with using a parameter set which is defined as a function of the number of the Ist nearest neighbors and the bond angles, which is determined by using genetic algorithm, the state is continuously changed with temperature." } @article{Knegtel_97, Title="Molecular docking to ensembles of protein structures", Author="R.M.A. Knegtel and I.D. Kuntz and C.M. Oshiro", Journal ="Journal of Molecular Biology", Volume ="266", Number ="2", Pages ="424--440", Year ="Feb. 21, 1997", Abstract = "Until recently, applications of molecular docking assumed that the macromolecular receptor exists in a single, rigid conformation. However, structural studies involving different ligands bound to the same target biomolecule frequently reveal modest but significant conformational changes in the-target. In this paper, two related methods for molecular docking are described that utilize information on conformational variability from ensembles of experimental receptor structures. One method combines the information into an ``energy-weighted average'' of the interaction energy between a ligand and each receptor structure. The other method performs the averaging on a structural level, producing a ``geometry-weighted average'' of the inter-molecular force field score used in DOCK 3.5. Both methods have been applied in docking small molecules to ensembles of crystal and solution structures, and we show that experimentally determined binding orientations and computed energies of known ligands can be reproduced accurately. The use of composite grids, when conformationally different protein structures are available, yields an improvement in computational speed for database searches in proportion to the number of structures." } @article{Mikulin_97, Title="Fitting reflectivity data from liquid crystal cells using genetic algorithms", Author ="D.J. Mikulin and D.A. Coley and J.R. Sambles", Journal ="Liquid Crystals", Volume ="22", Number ="3", Pages ="301--307", Year ="Mar. 1997", Abstract = "The half-leaky guided mode technique for quantifying thin optical layers is here combined with a data fitting routine based on a genetic algorithm to provide an immensely powerful procedure for detailing the director profile in liquid crystal cells. This approach not only provides a full description of the optical parameters of the cell, but also gives quantitative uncertainties in these parameters. It is tested here, first by fitting to theoretically produced data and then applied to real experimental data." } @article{Li_97, Title="Refinement of the {NMR} solution structure of the gamma-carboxyglutamic acid domain of coagulation factor {IX} using molecular dynamics simulation with initial {Ca2+} positions determined by a genetic algorithm", Author = "L.P. Li and T.A. Darden and S.J. Freedman and B.C. Furie and B. Furie and J.D. Baleja and H. Smith and R.G. Hiskey and L.G. Pedersen", Journal ="Biochemistry", Volume ="36", Number ="8", Pages ="2132--2138", Year ="1997", Abstract = "A genetic algorithm (GA) successfully identified the calcium positions in the crystal structure of bovine prothrombin fragment 1 bound with calcium ions (bfl/Ca). The same protocol was then used to determine the calcium positions in a closely related fragment, the Gla domain of coagulation factor IX, the structure of which had previously been determined by NMR spectroscopy in the presence of calcium ions. The most frequently occurring low-energy structure found by GA was used as the starting structure for a molecular dynamics refinement. The molecular dynamics simulation was performed using explicit water and the Particle-Mesh Ewald method to accommodate the long-range electrostatic forces. While the overall conformation of the NMR structure was preserved, significant refinement is apparent when comparing the simulation average structure with its NMR precursor in terms of the N-terminal (Tyr1-N) network, the total number of hydrogen bonds, the calcium ion coordinations, and the compactness of the structure. It is likely that the placement of calcium ions in the protein is critical for refinement. The calcium ions apparently induce structural changes during the course of the simulation that result in a more compact structure." } @article{Gunn_97, Title="Sampling protein conformations using segment libraries and a genetic algorithm", Author ="J.R. Gunn", Journal ="Journal of Chemical Physics", Volume ="106", Number ="10", Pages ="4270--4281", Year ="1997", Abstract = "We present a new simulation algorithm for minimizing empirical contact potentials for a simplified model of protein structure. The model consists of backbone atoms only (including C-beta) with the phi and psi dihedral angles as the only degrees of freedom. In addition, phi and psi are restricted to a finite set of 532 discrete pairs of values, and the secondary structural elements are held fixed in ideal geometries. The potential function consists of a leak-up table based on discretized inter-residue atomic distances. The minimization consists of two principal elements: the use of preselected lists of trial moves and the use of a genetic algorithm. The trial moves consist of substitutions of one or two complete loop regions, and the lists are in turn built up using preselected lists of randomly-generated three-residue segments. The genetic algorithm consists of mutation steps (namely, the loop replacements), as well as a hybridization step in which new structures an created by combining parts of two ''parents'' and a selection step in which hybrid structures are introduced into the population. These methods are combined into a Monte Carlo simulated annealing algorithm which has the overall structure of a random walk on a restricted set of preselected conformations. The algorithm is tested using two types of simple model potential. The first uses global information derived from the radius of gyration and the rms deviation to drive the folding, whereas the second is based exclusively on distance-geometry constraints. The hierarchical algorithm significantly outperforms conventional Monte Carlo simulation for a set of test proteins in both cases, with the greatest advantage being for the largest molecule having 193 residues. When tested an a realistic potential function, the method consistently generates structures ranked lower than the crystal structure. The results also show that the improved efficiency of the hierarchical algorithm exceeds that which would be anticipated from tests on either of the two main elements used independently." } @article{Raymer_97, Title="Predicting conserved water-mediated and polar ligand interactions in proteins using a $K$-nearest-neighbors genetic algorithm", Author ="M.L. Raymer and P.C. Sanschagrin and W.F. Punch and S. Venkataraman and E.D. Goodman and L.A. Kuhn", Journal ="Journal of Molecular Biology", Volume ="265", Number ="4", Pages ="445--464", Year ="1997", Abstract = "Water-mediated ligand interactions are essential to biological processes, from product displacement in thymidylate synthase to DNA recognition by Trp repressor, yet the structural chemistry influencing whether bound water is displaced or participates in ligand binding is not well characterized. Consolv, employing a hybrid k-nearest-neighbors classifier/genetic algorithm, predicts bound water molecules conserved between free and ligand-bound protein structures by examining the environment of each water molecule in the free structure. Four environmental features are used: the water molecule's crystallographic temperature factor, the number of hydrogen bonds between the water molecule and protein, and the density and hydrophilicity of neighboring protein atoms. After training on 13 non-homologous proteins, Consolv predicted the conservation of active-site water molecules upon ligand binding with 75% accuracy (Matthews coefficient C-m = 0.41) for seven new proteins. Mispredictions typically involved water molecules predicted to be conserved that were displaced by a polar ligand atom, indicating that Consolv correctly assesses polar binding sites; 90% accuracy (C-m = 0.78) was achieved for predicting conserved active-site water or polar ligand atom binding. Consolv thus provides an accurate means for optimizing ligand design by identifying sites favored to be occupied by either a mediating water molecule or a polar ligand atom, as well as water molecules likely to be displaced by the ligand. Accuracy for predicting first-shell water conservation between independently determined structures was 61% (C-m = 0.23). The ability to predict water-mediated and polar interactions from the free protein structure indicates the surprising extent to which the conservation or displacement of active-site bound water is independent of the ligand, and shows that the protein micro-environment of each water molecule is the dominant influence.", } @article{vanKampen_96, Title="Lethalization, penalty and repair functions for constraint handling in the genetic algorithm methodology", Author=" A.H.C. vanKampen and C.S. Strom and L.M.C Buydens", Journal ="Chemometrics And Intelligent Laboratory Systems", Volume ="34", Number ="1", Pages ="55--68", Year = "1996", Abstract = "A genetic algorithm was designed to find low energy distributions of ions above a crystal surface. To solve this constrained optimization problem, several constrained handling techniques were applied, i.e., lethalization, penalty and repair functions. It was shown that the simple lethalization scheme performs very well, and was at least comparable to some of the penalty functions. This was unexpected because, in general, it is believed that a severe penalization (i.e., lethalization) leads to poor results. An analysis of the fitnesses of trial distributions that violated a constraint as a function of the time, suggested that the properties of genetic based search were responsible for this result. From this it was concluded that a genetic algorithm in combination with lethalization may be an good choice to solve constrained optimization problems if the design of optimal penalty functions is difficult or impossible." } @article{Meza_96, Title="A comparison of a direct search method and a genetic algorithm for conformational searching", author ="J.C. Meza and R.S. Judson and T.R. Faulkner and A.M. Treasurywala", journal ="Journal of Computational Chemistry", volume ="17", number ="9", pages ="1142--1151", year ="1996", Abstract = "We present results from the application of two conformational searching methods: genetic algorithms (GA) and direct search methods for finding low energy conformations of organic molecules. GAs are in a class of biologically motivated optimization methods that evolve a population of individuals in which individuals who are more ``fit'' have a higher probability of surviving into subsequent generations. The parallel direct search method (PDS) it a type of pattern search method that uses an adaptive grid to search for minima. Both methods found energies equal to or lower than the energy of the relaxed crystal structure in all cases, at a relatively small cost in CPU time. We suggest that either method would be a good candidate to find 3-D conformations in a large scale screening application.", KeyWordsPlus="SMALL MOLECULES" } @article{Dandekar_96, Title="Identifying the tertiary fold of small proteins with different topologies from sequence and secondary structure using the genetic algorithm and extended criteria specific for strand regions", Author ="T. Dandekar and P. Argos", Journal ="Journal of Molecular Biology", Volume ="256", Number ="3", Pages ="645--660", Year ="1996", Abstract = "Grid-free protein folding simulations based on sequence and secondary structure knowledge (using mostly experimentally determined secondary structure information but also analysing results from secondary structure predictions) were investigated using the genetic algorithm, a backbone representation, and standard dihedral angular conformations. Optimal structures are selected according to basic protein building principles. Having previously applied this approach to proteins with helical topology, we have now developed additional criteria and weights for beta-strand-containing proteins, validated them on four small beta-strand-rich proteins with different topologies, and tested the general performance of the method on many further examples from known protein structures with mixed secondary structural type and less than 100 amino acid residues. Topology predictions close to the observed experimental structures were obtaine d in four test cases together with fitness values that correlated with the similarity of the predicted topology to the observed struct ures. Root-mean-square deviation values of C-alpha atoms in the superposed predicted and observed structures, the latter of which had di fferent topologies, were between 4.5 and 5.5 Angstrom (2.9 to 5.1 Angstrom without loops). Including 15 further protein examples with uniq ue folds, root-mean-square deviation values ranged between 1.8 and 6.9 Angstrom with loop regions and averaged 5.3 Angstrom and 4. 3 Angstrom, including and excluding loop regions, respectively." } @article{Willett_95, Title="Genetic algorithms in molecular recognition and design", author ="P. Willett", Journal ="Trends in Biotechnology", Volume ="13", Number ="12", Pages ="516--521", Year ="1995", Abstract = "Genetic algorithms provide a novel tool for the investigation of combinatorial optimization problems. A genetic algorithm takes an initial set of possible starting solutions, and iteratively improves them by means of crossover and mutation operators that are related to those involved in Darwinian evolution. This approach is illustrated by reference to applications in molecular modelling, the docking of flexible ligands into protein active sites and de novo ligand design." } @article{May_95, Title="Improved genetic algorithm-based protein structure comparisons: Pairwise and multiple superpositions", Author ="A.C.W. May and M.S. Johnson", Journal ="Protein Engineering", Volume ="8", Number ="9", Pages ="873--882", Year ="1995", Abstract = "Three major improvements to a previously described method for automatic protein structure comparison are described. First, a limit to translations for the rigid-body superposition is now assigned according to the dimensions of the structures being compared. Second, examination of the effect of the gap penalty on the derivation of a sequence alignment corresponding to a given structure superposition has led to a method to evaluate alternative structure-based sequence alignments. Third, the pairwise procedure has been generalized to multiple structure alignment. This implementation of rigid-body superposition can recognize well documented distant relationships which hitherto have required consideration of additional features and properties as well as those relationships between proteins of different sizes. A much larger common scaffold or framework between six globins can be extracted than that obtained using a standard algorithm for multiple structure superposition." } @article{Tam_95, Title="{GAMATCH} - A Genetic Algorithm-Based Program For Indexing Crystal Faces", Author ="K.Y. Tam and R.G. Compton", Journal ="Journal of Applied Crystallography", Volume ="28", Pages ="640--645", Year = "1995", Abstract = "An intelligent genetic algorithm-based crystal-indexing program, GAMATCH, is described, by means of which the Miller indices of the relevant planes can be unambiguously identified using a set of interplanar angles. A two-step-divide-and-conquer strategy is employed and is found to speed up the convergence to the global solution. The program was tested using both hypothetical and centimetre-sized triphenylmethyl chloride crystals. The results obtained were compared to the expected indices and excellent agreement was noted." } @article{Lazar_97, title ="De novo design of the hydrophobic core of ubiquitin", author ="G.A. Lazar and J.R. Desjarlais and T.M. Handel", journal ="Protein Science", volume ="6", number ="6", pages ="1167--1178", year ="1997", Abstract ="We have previously reported the development and evaluation of a computational program to assist in the design of hydrophobic cores of proteins. In an effort to investigate the role of core packing in protein structure, we have used this program, referred to as Repacking of Cores (ROC), to design several variants of the protein ubiquitin. Nine ubiquitin variants containing from three to eight hydrophobic core mutations were constructed, purified, and characterized in terms of their stability and their ability to adopt a uniquely folded native-like conformation. In general, designed ubiquitin variants are more stable than control variants in which the hydrophobic core was chosen randomly. However, in contrast to previous results with 434 cro, all designs are destabilized relative to the wild-type (WT) protein. This raises the possibility that beta-sheet structures have more stringent packing requirements than alpha-helical proteins. A more striking observation is that all variants, including random controls, adopt fairly well-defined conformations, regardless of their stability. This result supports conclusions from the cro studies that non-core residues contribute significantly to the conformational uniqueness of these proteins while core packing largely affects protein stability and has less impact on the nature or uniqueness of the fold. Concurrent with the above work, we used stability data on the nine ubiquitin variants to evaluate and improve the predictive ability of our core packing algorithm. Additional versions of the program were generated that differ in potential function parameters and sampling of side chain conformers. Reasonable correlations between experimental and predicted stabilities suggest the program will be useful in future studies to design variants with stabilities closer to that of the native protein. Taken together, the present study provides further clarification of the role of specific packing interactions in protein structure and stability, and demonstrates the benefit of using systematic computational methods to predict core packing arrangements for the design of proteins." } @article{Dejarlais_95, title ="New Strategies in Protein Design", author ="J.R. Desjarlais and T.M. Handel", journal ="Current Opinion in Biotechnology", volume ="6", number = "4", pages = "460--466", year = "1995", Abstract = "Initially, it was hoped that very simple rules could be used to design proteins that embody all the characteristics of natural proteins. Indeed, with single-domain proteins as targets, it has been possible to design proteins that adopt the desired global fold. Yet, designed proteins with well defined structures and properties that mimic those of natural proteins remain elusive. Recent efforts in protein design have been directed toward addressing the basis for non-native characteristics in most protein designs. Although it is clear that specific tertiary interactions between all residues in a protein contribute to the final folded state, much attention has been placed on optimizing the packing of side chains in the hydrophobic core, with substantial success." } @article{Hirsch_95, Title="Fitting of Diffusion-Coefficients In A 3-Compartment Sustained-Release Drug Formulation Using A Genetic Algorithm", Author ="R. Hirsch and C.C. Mullergoymann", Journal ="International Journal of Pharmaceutics", Volume ="120", Number ="2", Pages ="229--234", Year ="1995", Abstract = "This article presents a method of fitting diffusion coefficients in a three-compartment drug formulation to data of concentration measurements. The volume of the central compartment is not constant, but increases with time up to a certain amount. The speed of growth is proportional to the actual distance from the final thickness. A model function based on Fick's second law of diffusion is used to describe the concentration with respect to location and time. In order to find the values of the diffusion coefficients they are encoded to data structures on which the mechanisms of evolution can be applied: mutation and selection. It is shown how the convergence speed is influenced by the optimization parameters: the more individuals are involved in the evolution process, the fewer the generations it takes the algorithm to fit the parameters. There are optimal values for the rate of mutation (m approximate to 0.008 bit(-1)) and the selection factor, which controls the influence of selection in the mating process. Its optimal value is less than unity, which means that the algorithm converges faster when sometimes the genetic information of the weaker of two individuals is passed on to the next generation.", AuthorKeywords = "DIFFUSION, FICKS 2ND LAW, LAMELLAR LIQUID CRYSTAL, SUSTAINED RELEASE, DIFFUSION COEFFICIENT, CURVILINEAR PARAMETER FITTING, GENETIC ALGORITH M" } @article{May_94, Title="Protein-Structure Comparisons Using A Combination of A Genetic Algorithm, Dynamic-Programming And Least-Squares Minimization", Author ="A.C.W. May and M.S. Johnson", Journal ="Protein Engineering", Volume ="7", Number ="4", Pages ="475--485", Year ="1994", Abstract = "We introduce a completely automatic and objective procedure for the comparison of protein structures. A genetic algorithm is used to search for a near optimal solution of the rigid-body superposition of two whole protein structures. The specification of an initial set of equivalences is not required. Topological equivalences in the final structural alignment are defined by a conventional dynamic programming routine, which is commonly used to compare protein sequences. A least-squares fitting algorithm is then used to optimize the fit between the final set of equivalences. We have applied our method to the comparison of ribonucleic acid structures, as well as protein structures. The structural alignments are generally consistent with those previously published. In fact, on most occasions our method defines at least the same number of topological equivalences as other procedures, but always with a lower r.m.s. distance between them." } @article{Hartke_93, Title="Global Geometry Optimization of Clusters Using Genetic Algorithms", Author ="B. Hartke", Journal ="Journal of Physical Chemistry", Volume ="97", Number ="39", Pages = "9973--9976", Year = "1993", Abstract = "A genetic algorithm is used to find the global minimum energy structure for Si4 on an empirical potential energy surface. Given a suitable encoding of the cluster geometry, and an exponential scaling of the potential energy values to obtain a fitness function, the genetic algorithm can successfully optimize all degrees of freedom. With the number of potential energy function evaluations as a measure, the genetic algorithm is more economical than either a set of traditional, local minimizations or a molecular dynamics simulated annealing approach." } @article{Zacharias_98, title="Combining genetic algorithm and simulated annealing: a molecular geometry optimization study", author ="C.R. Zacharias and M.R. Lemes and A.D. Pino", journal ="THEOCHEM-Journal of Molecular Structure", volume = "430", number ="29--39", year = "1998", abstract ="We introduce a new hybrid approach to determine the ground state geometry of molecular systems. Firstly, we compared the ability of genetic algorithm (GA) and simulated annealing (SA) to find the lowest energy geometry of silicon clusters with six and 10 atoms. This comparison showed that GA exhibits fast initial convergence, but its performance deteriorates as it approaches the desired global extreme. Interestingly, SA showed a complementary convergence pattern, in addition to high accuracy. Our new procedure combines selected features from GA and SA to achieve weak dependence on initial parameters, parallel search strategy, fast convergence and high accuracy. This hybrid algorithm outperforms GA and SA by one order of magnitude for small silicon clusters (Sib and Si lo) Next, we applied the hybrid method to study the geometry of a 20-atom silicon cluster. It was able to find an original geometry, apparently lower in energy than those previously described in literature. In principle, our procedure can be applied successfully to any molecular system." } @article{Fu_97, title = "Surface reconstruction of {Si} (001) by Genetic Algorithm and simulated annealing method", author ="R.T. Fu and K. Esfarjani and Y. Hashi and J. Wu and X. Sun and Y. Kawazoe", journal ="Science Reports of The Research Institutes Tohoku University Series A-Physics Chemistry And Metallurgy", volume ="44", number ="1", pages ="77--81", year = "Mar. 1997", Abstract ="The Genetic Algorithm (GA) is one of the most recently developed techniques to find the ''Global'' minimum of an energy functional. This technique combined with conjugated gradient or molecular dynamics has been demonstrated to be efficient for the ground-state configuration search in materials research, e.g. fullerene formation, in this paper, based on the generalized tight-binding molecular dynamics, we apply the GA to study the surface reconstruction of Silicon (001) for the first time. Up to 65 generations, the ''Global'' minimum or the ground-state configuration for the surface reconstruction of Si (001) was detected efficiently in our GA simulation. Id our tight-binding model, a perfect symmetry-dimer structure was found to be the most energetic while some defect asymmetry-dimer structure could coexist in the lists of candidate structures due to the thermal defect or charge transfer which was described with the smearing parameter empirically. We also perform the more traditional Simulated Annealing (SA) technique to deal with the same problem. The results in terms of efficiency, accuracy of the ground-state reconstructed surface and CPU time are compared." } @article{Clark_96, title="Evolutionary algorithms in computer-aided molecular design", author = "D.E. Clark and D.R. Westhead", journal ="Journal of Computer-aided Molecular Design", volume ="10", number = "4", pages ="337--358", year ="1996", Abstract = "In recent years, search and optimisation algorithms inspired by evolutionary processes have been applied with marked success to a wide variety of problems in diverse fields of study. In this review, we survey the growing application of these 'evolutionary algorithms' in one such area: computer-aided molecular design. In the course of the review, we seek to summarise the work to date and to indicate where evolutionary algorithms have met with success and where they have not fared so well. In addition to this, we also attempt to discern some future trends in both the basic research concerning these algorithms and their application to the elucidation, design and modelling of chemical and biochemical." } @article{Niesse_96, title = "Global geometry optimization of atomic clusters using a modified genetic algorithm in space-fixed coordinates", author = "J.A. Niesse and H.R. Mayne", journal ="Journal of Chemical Physics", volume ="105", number = "11", pages = "4700--4706", year = "1996", Abstract = "In a recent paper, Gregurick, Alexander, and Hartke [S. K. Gregurick, M. H. Alexander, and B. Hartke, J. Chem. Phys. 104, 2684 (1996)] proposed a global geometry optimization technique using a modified Genetic Algorithm approach for clusters. They refer to their technique as a deterministic/stochastic genetic algorithm (DS-GA). In this technique, the stochastic part is a traditional GA, with the manipulations being carried out on binary-coded internal coordinates (atom-atom distances). The deterministic aspect of their method is the inclusion of a coarse gradient descent calculation on each geometry. This step avoids spending a large amount of computer time searching parts of the configuration space which correspond to high-energy geometries. Their tests of the technique show it is vastly more efficient than searches without this local minimization. They report geometries for clusters of up to n = 29 Ar atoms, and find that their computer time scales as O(n(4.5)). In this work, we have recast the genetic algorithm optimization in space-fixed Cartesian coordinates, which scale much more favorably than internal coordinates for large clusters. We introduce genetic operators suited for real (base-10) variables. We find convergence for clusters up to n = 55. Furthermore, our algorithm scales as O(n(3.3)). It is concluded that genetic algorithm optimization in nonseparable real variables is not only viable, but numerically superior to that in internal candidates for atomic cluster calculations. Furthermore, no special choice of variable need be made for different cluster types; real Cartesian variables are readily portable, and can be used for atomic and molecular clusters with no extra effort." } @article{Deaven_95, title = "Molecular-Geometry Optimization With A Genetic Algorithm", author = "D.M. Deaven and K.O. Ho", journal = "Physical Review Letters", volume = "75", number = "2", pages = "288--291", year ="1995" } @Misc{Hesser1991, CROSSREF = {Schwefel1991}, AUTHOR = {J\"urgen Hesser and Reinhard M\"anner}, TITLE = {Towards an Optimal Mutation Probability for Genetic Algorithms}, PAGES = {23--32} } @Misc{Muehlenbein1993aa, AUTHOR = {Heinz M\"uhlenbein and Dirk Schlierkamp-Voosen}, TITLE = {Optimal Interaction of Mutation and Crossover in the Breeder Genetic Algorithm}, PAGES = {648}} @Misc{Culberson1993, AUTHOR = {Joseph C. Culberson}, TITLE = {Crossover versus Mutation: Fueling the Debate: {T}{G}{A} versus {G}{I}{G}{A}}, PAGES = {632} } @article{Maddox_95, title = "Genetics Helping Molecular-Dynamics", author = "J. Maddox", journal = "Nature", volume = "376", number = "6537", pages = "209--209", year = "1995" } @article{Deaven_96, title ="Structural optimization of {Lennard-Jones} clusters by a genetic algorithm", author ="D.M. Deaven and N. Tit and J.R. Morris and K.M. Ho", journal ="Chemical Physics Letters", volume ="256", number ="1--2", pages ="195--200", year ="1996", Abstract = "We use a newly-developed genetic algorithm to determine the lowest energy atomic configurations of 2-100 atoms in the {Lennard-Jones} potential. Our method, which contains no bias to specific symmetries, yields structures which are identical to or are lower in energy than all previously published structures." } @article{Morris_96, title="Genetic-Algorithm Energy Minimization For Point Charges On A Sphere", author ="J.R. Morris and D.M. Deaven and K.M. Ho", journal ="Physical Review B-Condensed Matter", volume ="53", number ="4", pages ="R1740--R1743", year ="1996", Abstract ="We Demonstrate That A Recently Developed Approach For Optimizing Atomic Structures Is Very Effective For Attacking The Thomson Problem of Finding The Lowest-Energy Configuration of N Point Charges On A Unit Sphere. Our Approach Uses A Genetic Algorithm, Combined With A ''Cut And Paste'' Scheme of Mating, That Efficiently Explores The Different Low-Energy Structures. Not Only Have We Reproduced The Known Results For 10 Less Than Or Equal To N Less Than Or Equal To 132 , This Approach Has Allowed Us To Extend The Calculation For All N Less Than Or Equal To 200. This Has Allowed Us To Identify Series of ''Magic'' Numbers, Where The lowest-Energy Structures Are Particularly Stable. Most of These Structures Are Icosahedral, But We Also Find Low-Energy Structures That Deviate From Icosahedral Symmetry." } @article{Wacker_98, title ="Structures of medium-sized silicon clusters", author ="K.M. Ho and A.A. Shvartsburg and B.C. Pan and Z.Y. Lu and C.Z. Wang and J.G. Wacker and J.L. Fye and M.F. Jarrold", journal = "Nature", volume ="392", number ="6676", pages ="582--585", year ="1998", Abstract = "Silicon is the most important semiconducting material in the microelectronics industry, If current miniaturization trends continue, minimum device features will soon approach the size of atomic clusters. In this size regime, the structure and properties of materials often differ dramatically from those of the hulk, An enormous effort has been devoted to determining the structures of free silicon clusters(1-22). Although progress has been made for Si-n with n < 8, theoretical predictions for larger clusters are contradictory(2-22) and none enjoy any compelling experimental support, Here we report geometries calculated for medium-sized silicon clusters using an unbiased global search with a genetic algorithm. Ion mobilities(23) determined for these geometries by trajectory calculations are in excellent agreement,vith the values that we measure experimentally, The cluster geometries that we obtain do not correspond to fragments of the hulk, For n = 12-18 they are built on a structural motif consisting of a stack of Si-9 tricapped trigonal prisms, For n greater than or equal to 19, our calculations predict that near-spherical cage structures become the most stable, The transition to these more spherical geometries occurs in the measured mobilities for slightly larger clusters than in the calculations, possibly because of entropic effects." } @article{Pullan_97, title ="Structure prediction of benzene clusters using a genetic algorithm", author ="W.J. Pullan", journal ="Journal of Chemical Information and Computer Sciences", volume ="37", number ="6", pages = "1189--1193", year ="1997", Abstract = "This paper describes a real coded, parallel genetic algorithm implemented to find global minimum energy structures of clusters of benzene (C6H6) molecules. Starting from randomly generated structures, the genetic algorithm was able to find minimum energy structures for clusters of two to fifteen benzene molecules." } @article{Hobday_97, title="Optimisation of carbon cluster geometry using a genetic algorithm", author ="S. Hobday and R. Smith", journal ="Journal of The Chemical Society-Faraday Transactions", volume ="93", number ="22", pages ="3919--3926", year ="1997", Abstract = "A genetic algorithm (GA) based global optimisation procedure has been developed and used to find the most stable configurations of small carbon clusters. The CA attempts to locate the set of atomic nuclei coordinates associated with the global minimum of the potential-energy function using an analogy to Darwinian natural selection. This algorithm uses a novel encoding scheme to evolve a population of cluster geometries towards a low-energy final state. Two semi-empirical many-body potential-energy functions have been encoded for carbon interactions. The binding energies and structural forms of carbon clusters between C-3 and C-60 are reported. It has been shown that the algorithm can determine structures with a lower energy than those previously published using more classical local optimisation procedures. The GA can also be used to predict the global minimal energy configuration of pairwise interaction potentials." } @article{Pucello_97, title="Search of molecular ground state via genetic algorithm: Implementation on a hybrid {SIMD-MIMD} platform", author = "N. Pucello and M. Rosati and G. D'Agostino and F. Pisacane and V. Rosato and M. Celino", journal = "International Journal of Modern Physics C", volume ="8", number ="2", pages ="239--252", year ="1997", abstract = "A genetic algorithm for the optimization of the ground-state structure of a metallic cluster has been developed and ported on a SIMD-MIMD parallel platform. The SIMD part of the parallel platform is represented by a Quadrics/APE100 consisting of 512 floating point units, while the MIMD part is formed by a cluster of workstations. The proposed algorithm is composed by a part where the genetic operators are applied to the elements of the population and a part which performs a further local relaxation and the fitness calculation via Molecular Dynamics. These parts have been implemented on the MIMD and on the SIMD part, respectively. Results have been compared to those generated by using Simulated Annealing" } %% Added by Peter Merz % Landscapes @article{Weinberger91b, author = "Edward D. Weinberger", title = "{Local Properties of Kauffman's N-k model: A tunably Rugged Enegy Landscape}", journal = "Physical Review A", volume = "44", number = "10", pages = "6399--6413", year = "1991", } @InProceedings{Wright32, author = "S. Wright", title = "{The Roles of Mutation, Inbreeding, Crossbreeding, and Selection in Evolution}", volume = "1", pages = "365", booktitle = "Proceedings of the Sixth Congress on Genetics", year = "1932", } @article{Weinberger91, author = "Edward D. Weinberger", title = "{Correlated and Uncorrelated Fitness Landscapes and How to Tell the Difference}", journal = "Biological Cybernetics", volume = "63", pages = "325--336", year = "1990", } @Article{Reeves97, author = "C. R. Reeves", title = "{Landscapes, Operators and Heuristic Search}", journal = "Annals of Operations Research", year = "1998", note = "To appear.", } @article{Stadler:92d, author = "Peter F. Stadler", title = "{Correlation in Landscapes of Combinatorial Optimization Problems}", journal = {Europhys.\ Lett.}, volume = {20}, pages = {479-482}, year = {1992}, } @inproceedings{Stadler:95c, author = {Peter F. Stadler}, title = "{Towards a Theory of Landscapes}", pages = {77-163}, editor = {R. {Lop{\'e}z-Pe{\~n}a} and R. Capovilla and R. Garc{\'\i}a-Pelayo and H. Waelbroeck and F. Zertuche}, booktitle = {Complex Systems and Binary Networks}, publisher = {Springer Verlag}, address = {Berlin, New York}, year = {1995}, series = {Lecture Notes in Physics}, volume = {461}, note = {SFI preprint 95-03-030}, } @article{Stadler:96b, author = {Peter F. Stadler}, title = "{Landscapes and their Correlation Functions}", journal = {J.\ Math.\ Chem.}, pages = {1-45}, volume = {20}, year = {1996}, note = {SFI preprint 95-07-067}, } @Article{Angel98, author = "E. Angel and V. Zissimopoulos", title = "{Autocorrelation Coefficient for the Graph Bipartitioning Problem}", journal = "Theoretical Computer Science", volume = "191", pages = "229--243", year = "1998", } @Article{Davidor90b, key = "Davidor", author = "Yuval Davidor", title = "{Epistasis Variance: Suitability of a Representation to Genetic Algorithms}", journal = "Complex Systems", pages = "369--383", volume = "4", number = "4", year = "1990", } @Book{Kauffman93, author = "S. A. Kauffman", title = "The Origins of Order: Self-Organization and Selection in Evolution.", publisher = "Oxford University Press", year = "1993", keywords = "self organization, organisation, OUP, GA, genetic algorithm, chaos, text, book, emergent", abstract = "via enews", } @Book{Englemore_Morgan_88, author = "R. Englemore and T. Morgan (eds.)", title = "Blackboard Systems", publisher = "Addison-Wesley", year ="1988" } @Article{Kauffman87b, author = "S. A. Kauffman and S. Levin", title = "{Towards a General Theory of Adaptive Walks on Rugged Landscapes}", journal = "Journal of Theoretical Biology", volume = "128", pages = "11--45", year = "1987", } @InProceedings{JonesForrest95, author = "T. Jones and S. Forrest", title = "{Fitness Distance Correlation as a Measure of Problem Difficulty for Genetic Algorithms}", pages = "184--192", editor = "L. J. Eshelman", booktitle = "Proceedings of the 6th International Conference on Genetic Algorithms", publisher = "Morgan Kaufmann", year = "1995" } % EA books @Book{Holland75:book, author = "J. Holland", title = "Adaptation in Natural and Artificial Systems.", publisher = "University of Michigan Press", year = "1975" } @Book{Rechenberg73:book, author = "I. Rechenberg", title = "Evolutionsstrategie: Optimierung technischer Systeme nach Prinzipien der biologischen Evolution", publisher = "Frommann-Holzboog", year = "1973", address = "Stuttgart" } @Book{Fogel66:book, author = "L. J. Fogel and A. J. Owens and M. J. 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Joosen", booktitle = "Proceedings of High-Performance Computing and Networking: International Conference and Exhibition, Amsterdam, The Netherlands , April 21-23, 1998 ", editor = "P. Sloot and M. Bubak and B. Hertzberger", pages = "843--853", series = "Lecture Notes in Computer Science", year = "1998", publisher = "Springer, Berlin", volume = "1401", abstract = "In this paper, we present a multi-agent approach to modelling genetic algorithms (GAs). GAs let a population of chromosomes evolve in order to optimise a given objective function. We model chromosomes as autonomous agents, that are themselves responsible for applying the genetic operators. Moreover, they are further enhanced by adding local search and adaptive behaviour. These extensions lead to the concept of Genetic Search Agents. We illustrate the expressive power of the Correlate language and runtime system in which we implemented our agents. Experiments with the Travelling Salesman Problem show the power of Genetic Search Agents, outperforming both distributed GAs and parallel local search." } %%% % % Added by Carlos Cotta % and Pablo (09/Aug/2000) % %% @article{Minsky_94, title = "Negative Expertise", author = "M. Minsky", journal = "International Journal of Expert Systems", volume = "7", number = "1", pages = "13--19", year = "1994" } @article{Johnson_Papadimitriou_Yannakakis_88, author = "D.S. Johnson and C.H. Papadimitriou and M. Yannakakis", title = "How easy is local search~?", journal = "Journal of Computers and System Sciences", volume = "37", year = "1988", pages = "79-100" } @Incollection{Yannakakis_LS_complexity_survey, author = "M. Yannakakis", title = "Computational Complexity", booktitle = "Local Search in Combinatorial Optimization", year = "1997", pages = "19--55", editor = "E.H.L. Aarts and J.K. Lenstra", publisher = "Wiley, Chichester" } @book{Papadimitriou_Steiglitz_82, title = "Combinatorial Optimization: Algorithms and Complexity", author = "C.H. Papadimitriou and K. Steiglitz", publisher = "Prentice-Hall, Inc.", address = "Englewood Cliffs, New Jersey", year = "1982" } @article{Lin_65, title = "Computer Solutions of the Traveling Salesman Problem", author = "S. Lin", journal = "Bell System Technical Journal", volume = "10", number = "", pages = "2245--2269", year = "December 1965" } @techreport{Goldstein_Lesk_75, title = "Common Feature Techniques for Discrete Optimization", author = "A.J. Goldstein and A.B. Lesk", type = "Comp. Sci. Tech. Report", number = "27", institution = "Bell. Tel. Labs", year = "March 1975" } @book{Lewis_Papadimitriou_98, author = "H.R. Lewis and C.H. 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Begin", editor = {Mercer, R.E. and Neufeld, E.}, booktitle = {Advances in Artificial Intelligence. 12th Biennial Conference of the Canadian Society for Computational Studies of Intelligence}, publisher = {Springer-Verlag}, address = {Berlin}, pages = {114--127}, year = {1998}, } @InProceedings{KRT97, title = {Vector quantization using genetic K-means algorithm for image compression}, author = {Krishna, K. and Ramakrishnan, K.R. and Thathachar, M.A.L.}, booktitle = {1997 International Conference on Information, Communications and Signal Processing}, publisher = {IEEE}, address = {New York, NY}, pages = {1585--1587}, volume = {3}, year = {1997}, } @InProceedings{JH99, title = {Dynamic vehicle routing using hybrid genetic algorithms}, author = {Jih, W.R. and Hsu, Y.J.}, booktitle = {Proceedings of the 1999 Congress on Evolutionary Computation}, year = {1999}, publisher = {IEEE}, address = {Washington D.C.}, pages = {453--458}, } @InProceedings{Gri99, title = {Hybrid genetic algorithms for analogue network synthesis}, author = {Grimbleby, J.B.}, booktitle = {Proceedings of the 1999 Congress on Evolutionary Computation}, year = {1999}, publisher = {IEEE}, address = {Washington D.C.}, pages = {1781--1787}, } @InProceedings{QV98, title = {Hybrid genetic algorithms as tools for complex optimisation problems}, author = {Quagliarella, D. and Vicini, A.}, editor = {Blonda, P. and Castellano, M. and Petrosino, A.}, booktitle = {New Trends in Fuzzy Logic II. Proceedings of the Second Italian Workshop on Fuzzy Logic}, publisher = {World Scientific}, address = {Singapore}, pages = {300--307}, year = {1998}, } @Article{GIY98, title = {Bicriteria transportation problem by hybrid genetic algorithm}, author = "M. Gen and K. Ida and L. Yinzhen", journal = {Computers \& Industrial Engineering}, volume = {35}, number = {1-2}, pages = {363--366}, year = {1998}, } @InProceedings{IK98, title = {Learning of neural networks with parallel hybrid {GA} using a {R}oyal {R}oad function}, author = "T. Ichimura and Y. Kuriyama", booktitle = {1998 IEEE International Joint Conference on Neural Networks}, publisher = {IEEE}, address = {New York, NY}, pages = {1131--1136}, volume = {2}, year = {1998}, } @InProceedings{CTO97, title = {Time efficient and robust {3-D} brain image centering and realignment using hybrid genetic algorithm}, author = {Cadieux, S. and Tanizaki, N. and Okamura, T.}, booktitle = {Proceedings of the 36th SICE Annual Conference}, publisher = {IEEE}, pages = {1279--1284}, year = {1997}, } @Article{ADR-S98, title = {Service restoration in compensated distribution networks using a hybrid genetic algorithm}, author = {Augugliaro, A. and Dusonchet, L. and Riva-Sanseverino, E.}, journal = {Electric Power Systems Research}, volume = {46}, number = {1}, pages = {59--66}, year = {1998}, } @Article {HBM98, title = {Optimization of beam orientation in radiotherapy using planar geometry}, author = {Haas, O.C.L. and Burnham, K.J. and Mills, J.A.}, journal = {Physics in Medicine and Biology}, volume = {43}, number = {8}, pages = {2179--2193}, year = {1998}, } @Article {Bos98, title = {Aircraft conceptual design by genetic/gradient-guided optimization}, author = {Bos, A.H.W.}, journal = {Engineering Applications of Artificial Intelligence}, volume = {11}, number = {3}, pages = {377--382}, year = {1998}, } @Article{MWC99, title = {A hybrid simplex genetic algorithm for estimating geoacoustic parameters using matched-field inversion}, author = {Musil, M. and Wilmut, M.J. and Chapman, N.R.}, journal = {{IEEE} Journal of Oceanic Engineering}, volume = {24}, number = {3}, pages = {358--369}, year = {1999}, } @Article{WRWH99, title = {The impact of approximate evaluation on the performance of search algorithms for warehouse scheduling}, author = {Watson, J.P. and Rana, S. and Whitley, L.D. and Howe, A.E.}, journal = {Journal of Scheduling}, volume = {2}, number = {2}, pages = {79--98}, year = {1999}, } @Article{RHH99, title = {Volume estimation from sparse planar images using deformable models}, author = {Ruff, C.F. and Hughes, S.W. and Hawkes, D.J.}, journal = {Image and Vision Computing}, volume = {17}, number = {8}, pages = {559--565}, year = {1999}, } @Article{AC98, title = {Resolution of pattern recognition problems using a hybrid genetic/random neural network learning algorithm}, author = {Aguilar, J. and Colmenares, A.}, journal = {Pattern Analysis and Applications}, volume = {1}, number = {1}, pages = {52--61}, year = {1998}, } @Article{WM99, title = {Design of doubly periodic filter and polarizer structures using a hybridized genetic algorithm}, author = {Weile, D.S. and Michielssen, E.}, journal = {Radio Science}, volume = {34}, number = {1}, pages = {51--63}, year = {1999}, } @Article{Ozd99, title = {A genetic algorithm approach to a general category project scheduling problem}, author = {Ozdamar, L.}, journal = {IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews)}, volume = {29}, number = {1}, pages = {44--59}, year = {1999}, } @Article{MC98, title = {Identical parallel machine scheduling problem for minimizing the makespan using genetic algorithm combined with simulated annealing}, author = {Min, L. and Cheng, W.}, journal = {Chinese Journal of Electronics}, volume = {7}, number = {4}, pages = {317--321}, year = {1998}, } @Article{HI98, title = {Automatic design of frequency sampling filters by hybrid genetic algorithm techniques}, author = {Harris, S.P. and Ifeachor, E.C.}, journal = {IEEE Transactions on Signal Processing}, volume = {46}, number = {12}, pages = {3304--3314}, year = {1998}, } @Article{MM00, title = {A hybrid Hopfield network-genetic algorithm approach to optimal process plan selection}, author = {Ming, X.G. and Mak, K.L.}, journal = {International Journal of Production Research}, volume = {38}, number = {8}, pages = {1823--1839}, year = {2000}, } @Article{WK00, title = {A hybrid genetic algorithm for global solution of nondifferentiable nonlinear function}, author = {Wei, X. and Kangling, F.}, journal = {Control Theory \& Applications}, volume = {17}, number = {2}, pages = {180--183}, year = {2000}, } @Article{SCPN00, title = {Development of an intelligent technique for traffic network incident detection}, author = {Srinivasan, D. and Cheu, R.L. and Poh, Y.P. and Ng, A.K.C.}, journal = {Engineering Applications of Artificial Intelligence}, volume = {13}, number = {3}, pages = {311--322}, year = {2000}, } @Article{YKN99, title = {Estimation of impulse response of vocal tract using hybrid genetic algorithm-a case of only glottal source}, author = {Yoneyama, M. and Komori, H. and Nakamura, S.}, journal = {Journal of the Acoustical Society of Japan}, volume = {55}, number = {12}, pages = {821--830}, year = {1999}, } @Article{NCG00, title = {A continuous approach to the design of physical distribution systems}, author = {Novaes, A.G.N. and De-Cursi, J.E.S. and Graciolli, O.D.}, journal = {Computers \& Operations Research}, volume = {27}, number = {9}, pages = {877--893}, year = {2000}, } @Article{Ost99c, title = {A neuro-genetic algorithm for heteroskedastic time-series processes: empirical tests on global asset returns}, author = {Ostermark, R.}, journal = {Soft Computing}, volume = {3}, number = {4}, pages = {206--220}, year = {1999}, } @Article{MCPB00, title = {Hybrid genetic optimization and statistical model based approach for the classification of shadow shapes in sonar imagery}, author = {Mignotte, M. and Collet, C. and P\'erez, P. and Bouthemy, P.}, journal = {{IEEE} Transactions on Pattern Analysis and Machine Intelligence}, volume = {22}, number = {2}, pages = {129--141}, year = {2000}, } @Article{DJ00, title = {Solving large unconstrained multilevel lot-sizing problems using a hybrid genetic algorithm}, author = {Dellaert, N. and Jeunet, J.}, journal = {International Journal of Production Research}, volume = {38}, number = {5}, pages = {1083--1099}, year = {2000}, } @Article{KMV00, title = {A hybrid genetic approach for channel reuse in multiple access telecommunication networks}, author = {Kassotakis, I.E. and Markaki, M.E. and Vasilakos, A.V.}, journal = {{IEEE} Journal on Selected Areas in Communications}, volume = {18}, number = {2}, pages = {234--243}, year = {2000}, } @Article{MCML99, title = {A hybrid genetic algorithm for the single machine scheduling problem}, author = {Miller, D.M. and Chen, H.C. and Matson, J. and Liu, Q.}, journal = {Journal of Heuristics}, volume = {5}, number = {4}, pages = {437--454}, year = {1999}, } @Article{KR99, title = {Hybrid genetic algorithm for transmitter location in wireless networks}, author = {Krzanowski, R.M. and Raper, J.}, journal = {Computers, Environment and Urban Systems}, volume = {23}, number = {5}, pages = {359--382}, year = {1999}, } @Article{UGSFL99, title = {A hybrid genetic algorithm for optimal reactive power planning based upon successive linear programming}, author = {Urdaneta, A.J. and G\'omez, J.F. and Sorrentino, E. and Flores, L. and D\'{\i}az, R.}, journal = {{IEEE} Transactions on Power Systems}, volume = {14}, number = {4}, pages = {1292--1298}, year = {1999}, } @Article{H-ABM99, title = {A hybrid genetic/optimization algorithm for a task allocation problem}, author = {Hadj-Alouane, A.B. and Bean, J.C. and Murty, K.G.}, journal = {Journal of Scheduling}, volume = {2}, number = {4}, year = {1999}, } @Article{WC99, title = {A hybrid genetic algorithm for function optimization}, author = {Wei, P. and Cheng, L.X.}, journal = {Journal of Software}, volume = {10}, number = {8}, pages = {819--823}, year = {1999}, } @InCollection{BH91, author = {B\"ack, T. and Hoffmeister, F.}, title = {Adaptive Search by Evolutionary Algorithms}, booktitle = {Models of Selforganization in Complex Systems}, year = {1991}, editor = {Ebeling, W. and Peschel, M. and Weidlich, W.}, pages = {17--21}, series = {Mathematical Research}, number = {64}, publisher = {Akademie-Verlag}, } @InProceedings{CBFR99, author = {Crain, T. and Bishop, R. and Fowler, W. and Rock, K.}, title = {Optimal Interplanetary Trajectory Design Via Hybrid Genetic Algorithm/Recursive Quadratic Program Search}, booktitle = {Ninth AAS/AIAA Space Flight Mechanics Meeting}, year = {1999}, editor = {}, pages = {99-133}, address = {Breckenridge CO}, publisher = {}, } @article{Ersoy_Panwar93, author = {Ersoy, C. and Panwar, S.S.}, title = {Topological design of interconnected {LAN/MAN} networks}, journal = {IEEE Journal on Selected Areas in Communications}, volume = {11}, number = {8}, pages = {1172--1182}, year = {1993} } @InProceedings{Gottlieb_Kruse00, title = {Selection in Evolutionary Algorithms for the Traveling Salesman Problem}, author = {Gottlieb, J. and Kruse, T.}, booktitle = {ACM Symposium on Applied Computing 2000}, year = {2000}, editor = {Carroll, J. and Damiani, E. and Haddad, H. and Oppenheim, D.}, pages = {415--421}, publisher = {ACM Press} } @Misc{Quinn88, OPTauthor = {M.J.Quinn}, OPTtitle = {Designing Efficient Algorithms for Parallel Computers}, OPThowpublished = {Computer Science Series}, OPTyear = {1988}, OPTnote = {MCGraw-Hill, ISBN 0-07-100249-9}, } @InProceedings{Pettey89, author = {C.C. Pettey and M.R. Leuze}, title = {A Theoretical Investigation of a Parallel Genetic Algorithm}, booktitle = {Proceeding of the Third International Conference on Genetic Algorithms}, OPTpages = {398--405}, OPTyear = {1989} } @InProceedings{Gottlieb00, title = {Permutation-Based Evolutionary Algorithms for Multidimensional Knapsack Problems}, author = {Gottlieb, J.}, booktitle = {ACM Symposium on Applied Computing 2000}, year = {2000}, editor = {Carroll, J. and Damiani, E. and Haddad, H. and Oppenheim, D.}, pages = {408--414}, publisher = {ACM Press} } @Incollection {Karp72, booktitle = {Complexity of Computer Computations}, year = {1972}, title = {Reducibility among combinatorial problems}, pages = {85--103}, author = {Karp, R.M.}, editor = {Miller, R.E. and Thatcher, J.W.}, publisher = {Plenum}, address = {New York NY} } @article{Lia00, author = {Liaw, C.F.}, title = {A hybrid genetic algorithm for the open shop scheduling problem}, journal = {European Journal of Oprational Research}, volume = {124}, number = {1}, pages = {28--42}, year = {2000} } @book{Sait_Youssef95, author = {Sait, S.M. and Youssef, H.}, title = {{VLSI} Design Automation: Theory and Practice}, publisher = {McGraw-Hill Book Co. (copublished by IEEE)}, address = {Europe}, year = {2000} } @InCollection{Surry_Radcliffe96, title = {Inoculation to Initialise Evolutionary Search}, author = {Surry, P.D. and Radcliffe, N.J.}, booktitle = {Evolutionary Computing: AISB Workshop}, editor = {Fogarty, T.C.}, year = {1996}, series = {Lecture Notes in Computer Science}, number = {1143}, pages = {269--285}, publisher = {Springer-Verlag}, } @InProceedings{Louis_MVRP99, title = {Multiple Vehicle routing with Time Windows Using Genetic Algorithms}, author = {Louis, S.J. and Yin, X. and Yuan, Z.Y.}, booktitle = {Proceedings of the 1999 Congress on Evolutionary Computation}, year = {1999}, pages = {1804--1808}, publisher = {IEEE Neural Network Council - Evolutionary Programming Society - Institution of Electrical Engineers}, address = {Washington D.C.} } @InProceedings{icga87*108, author = "D. Whitley", title = "Using reproductive evaluation to improve genetic search and heuristic discovery", pages = "108--115", ISBN = "0-8058-0159-6", editor = "Grefenstette, J.J.", booktitle = "Proceedings of the Second International Conference on Genetic Algorithms and their Applications", address = "Cambridge, MA", month = jul, year = "1987", publisher = "Lawrence Erlbaum Associates", } @InProceedings{BrHuSp89, author = "D. Brown and C. Huntley and A. Spillane", editor = "J. Schaffer", title = "A {P}arallel {G}enetic {H}euristic for the {Q}uadratic {A}ssignment { P}roblem", booktitle = "Proceedings of the Third International Conference on Genetic Algorithms", year = "1989", publisher = "Morgan Kaufmann", pages = "406--415", } @Article{Wehrens93, author = "R. Wehrens and C. Lucasius and L. Buydens and G. Kateman", title = "{HIPS}, {A} Hybrid self-adapting expert system for nuclear magnetic resonance spectrum interpretation using genetic algorithms", journal = "Analytica Chimica ACTA", year = "1993", volume = "277", number = "2", pages = "313--324", month = may, } @InProceedings{TopchyAPLe1996a, author = "A.P. Topchy and O.A. Lebedko and V.V. Miagkikh", booktitle = "Proceedings of International Conference on Evolutionary Computation and its Applications", title = "Fast Learning in Multilayered Networks by means of Hybrid Evolutionary and Gradient Algorithms", year = "1996", abstract-url = "http://web.cps.msu.edu/~miagkikh/web/6.ASC", url = "http://web.cps.msu.edu/~miagkikh/web/6.ps.gz", keywords = "genetic algorithms, neural networks, evolutionary programming, cooperative evolution", month = jun, pages = "390--398", scope = "learn", } @InProceedings{icga97*489, author = "E. Ramat and G. Venturini and C. Lente and M. Slimane", title = "Solving the Multiple Resource Constrained Project Scheduling Problem with a Hybrid Genetic Algorithm", pages = "489--496", ISBN = "1-55860-487-1", editor = "B{\"a}ck, Th.", booktitle = "Proceedings of the Seventh International Conference on Genetic Algorithms", publisher = "Morgan Kaufmann", address = "San Francisco CA", year = "1997" } @Article{yao93evolutionary, author = "Yao, X.", title = "Evolutionary Artificial Neural Networks", journal = "Int. Journal of Neural Systems", year = "1993", volume = "4", number = "3", pages = "203--222", month = sep, class = "nn, learning, genetic, survey", abstract = "Combinations of NNs with evolutionary search procedures, e.g. genetic algorithms. 3 levels of evolution: of connection weights, of topology, of learning rule. Discusses representation issues/problems, GA vs. gradient search, hybrids, developmental rule representation, fractal representation, node-centered representation, evolution of transfer functions. Large bibliography (137 titles)", notes = "^^", } @InProceedings{Rei00, title = {Simulation of Imprecise Ordinary Differential Equations Using Evolutionary Algorithms}, author = {Reich, C.}, booktitle = {ACM Symposium on Applied Computing 2000}, year = {2000}, editor = {Carroll, J. and Damiani, E. and Haddad, H. and Oppenheim, D.}, pages = {428--432}, publisher = {ACM Press} } @InProceedings{RJ00, title = {A weighted coding in a Genetic Algorithm for the Degree-constrained Minimum Spanning Tree Problem}, author = {Raidl, G.R. and Julstron, B.A.}, booktitle = {ACM Symposium on Applied Computing 2000}, year = {2000}, editor = {Carroll, J. and Damiani, E. and Haddad, H. and Oppenheim, D.}, pages = {440--445}, publisher = {ACM Press} } @InCollection{RRCT98, title = {An Evolutionary and Local Search Algorithm for Planning Two Manipulators Motion}, author = {Ridao, M.A. and Riquelme, J. and Camacho, E.F. and Toro, M.}, editor = {Del Pobil, A.P. and Mira, J. and Ali, M.}, booktitle = {Tasks and Methods in Applied Artificial Intelligence}, year = {1998}, series = {Lecture Notes in Computer Science}, volume = {1416}, publisher = {Springer-Verlag}, address = {Berlin Heidelberg}, pages = {105-114} } @Article{XZ97, author = {Xiao, J. and Zhang, L.}, title = {Adaptive Evolutionary Planner/Navigator for Mobile Robots}, journal = {{IEEE} Transactions on Evolutionary Computation}, year = {1997}, volume = {1}, number = {1}, pages = {18--28}, } @Article{Boldrin_Saffiotti_99, author = {L. Boldrin and A. Saffiotti}, title = {A modal logic for merging partial belief of multiple reasoners}, journal = {Journal of Logic and Computation}, year = 1999, volume = 9, number = 1, pages = {81--103}, note = {Online at \texttt{http://www.aass.oru.se/$\sim$asaffio/}} } @InProceedings{CZ99, title = {Hybridisation of Neural Networks and Genetic Algorithms for Time-Optimal Control}, author = {Chaiyaratana, N. and Zalzala, A.M.S.}, booktitle = {Proceedings of the 1999 Congress on Evolutionary Computation}, year = {1999}, pages = {389--396}, publisher = {IEEE}, address = {Washington D.C.} } @InProceedings{PDG99, title = {Fuzzy-Genetic Algorithms and Mobile Robot Navigation Among static Obstacles}, author = {Pratihar, D.K. and Deb, K. and Ghosh, A.}, booktitle = {Proceedings of the 1999 Congress on Evolutionary Computation}, year = {1999}, pages = {327--334}, publisher = {IEEE}, address = {Washington D.C.} } @techreport{Lamma_Pereira_Riguzzi_MultiAgentLogic, author = "E. Lamma and L.M. Pereira and F. Riguzzi", title = {Multi-agent Logic Aided Lamarckian Learning}, year = {2000}, institution = {Dipartimento di Elettronica, Informatica e Sistemistica, University of Bologna (Italy)}, number = {DEIS-LIA-00-004}, note = {LIA Series no.~44, submitted for publication}, } @InProceedings{Walters_98, author = "T. Walters", title = "Repair and Brood Selection in the Traveling Salesman Problem", booktitle = "Proceedings of the Fifth International Conference on Parallel Problem Solving from Nature, Amsterdam, The Netherlands", editor = "A.E. Eiben and T. Back and M. Schoenauer and H.-P. Schwefel", series = "Lecture Notes in Computer Science", volume = "1498", publisher = "Springer-Verlag", pages = "813--822", year = "1998" } @inproceedings{Knowles00telecomworkshop, author = "J.D. Knowles and D.W. Corne", title = "{M}ultiobjective {A}pproaches to the {A}daptive {D}istributed {D}atabase {M}anagement {P}roblem", booktitle = "Proceedings of the SAB/PPSN Workshops (Evolutionary Computation in Telecommunications Workshop", editor = "D. Corne", year = "2000" } @inproceedings{Knowles00cec, author = "J.D. Knowles and D.W. Corne", title = "M-{PAES}: {A} {M}emetic {A}lgorithm for {M}ultiobjective {O}ptimization", booktitle = "Proceedings of the 2000 Congress on Evolutionary Computation (CEC00)", publisher = "IEEE Press", address = {Piscataway, NJ}, pages = "325--332", year = "2000", note = "Nominated by CEC Program Committe to be extended and submitted to Knowledge and Information Systems (KAIS) Journal" } @misc{Knowles00patent, author = "J. Knowles and D. Corne", title = "{O}ptimisation {M}ethod", howpublished = "European Patent EP00305549.8", note = "Date filed: 30th June", info = "This is a patent (filed by Joshua Knowles' sponsors, BT Plc.,) of the {M-PAES} algorithm", year = "2000" } @inproceedings{Knowles00memeticwshop, author = "J.D. Knowles and D.W. Corne", title = "A {C}omparison of {D}iverse {A}proaches to {M}emetic {M}ultiobjective {C}ombinatorial {O}ptimization", editor = "Annie S. Wu", booktitle = "Proceedings of the 2000 Genetic and Evolutionary Computation Conference Workshop Program", pages = "103--108", year = "2000" } @inproceedings{Knowles00ppsn, author = "J.D. Knowles and D.W. Corne and M.J. Oates", title = "On the {A}ssessment of {M}ultiobjective {A}pproaches to the {A}daptive {D}istributed {M}anagement {P}roblem", booktitle = "Proceedings of the Sixth International Conference of Parallel Problem Solving From Nature (PPSN VI)", publisher = "Springer-Verlag", address = "Berlin", pages = "869--878", year = "2000" } @article{Knowles00bttj, author = "J.D. Knowles and M.J. Oates and D.W. Corne", title = "Advanced {M}ultiobjective {E}volutionary {A}lgorithms {A}pplied to two {P}roblems in {T}elecommunications", journal = "BT Technology Journal", volume = "18", number = "4", pages = "51--65", publisher = "Kluwer Academic Publishers", month = "October", year = "2000" } @misc{Knowles00kais, author = "J.D. Knowles and D.W. Corne", title = "{B}enchmarking a {N}ew {M}emetic {A}lgorithm {F}ramework for {P}areto {M}ultiobjective {O}ptimization", note = "Submitted to {\em Knowledge and Information Systems\/}", year = "2000" } @InProceedings{Hodgson_00cec, author = "R.J.W. Hodgson", title = "Memetic Algorithms and the Molecular Geometry Optimization Problem", booktitle = "Proceedings of the 2000 {C}ongress on {E}volutionary {C}omputation", pages = "625--632", year = "2000", address = "Piscataway, NJ", publisher = "IEEE Service Center" } @InProceedings{Merz_Freisleben_QAP_99, author = "P. Merz and B. Freisleben", title = "{A Comparison of Memetic Algorithms, Tabu Search, and Ant Colonies for the Quadratic Assignment Problem}", booktitle = "1999 Congress on Evolutionary Computation (CEC'99)", editor = "Pete Angeline", publisher = "IEEE Press", address = "Piscataway, NJ, USA", year = "1999", pages = "2063--2070" } @mastersthesis{Hartmann_mastersthesis_99, author = "John W. Hartmann", title = "Low-thrust Trajectory Optimization using Stochastic Optimization Methods", school = "Graduate College of the University of Illinois at Urbana-Champaign", organisation = "Department of Aeronautical and Astronautical Engineering, UIUC Dynamics, Control and Design Group ", address = "Urbana-Champaign, Illinois, USA", advisor = "Prof. Victoria Coverstone-Carroll", year = "1999" } @article{Tanaka_Yamada_99, title = "Solving Multiobjective Time Tabling Problem by Using Requests", author = "M. Tanaka and M. Yamada", journal = "Transactions of Systems, Control and Information", volume = "12", number = "2", year = "1999", pages = "90--97", abstract = "In this paper, the time tabling problem of schools is discussed where the teachers, preference of time slots for each lecture is considered. The teachers' preference and the students' wishes are aggregated into two objectives, and the problem is treated as the two objectives of the multicriteria optimization problem. The problem is solved by using the framework of multiobjective genetic algorithm. The primary difficulty of this problem is how to satisfy the constraints. Here this problem is solved by using the local search for each individual that does not satisfy the constraints, and the revised ones are used in the next generation." } @InProceedings{Franca_Mendes_Moscato_98SOBRAPO, author = "P.M. {Fran\c{c}a} and A.S. Mendes and P. Moscato", title = "{Algoritmos Mem\'eticos e o Sequenciamento em M\'aquina Simples com Setup Times e Restri\c{c}\~oes de Datas de Entrega}", booktitle = "{XXX SOBRAPO} - {Simp\'osio Brasileiro de Pesquisa Operacional, Curitiba, PR, Brasil, 25-27 de Novembro}", pages = "315--316", year ="1998", publisher = "{Sociedade Brasileira de Pesquisa Operacional}", note = "extended abstract" } @InProceedings{Holstein_Moscato_98SOBRAPO, author = "D. Holstein and P. Moscato", title = "{Um Algoritmo Mem\'etico que utiliza Busca Local Guiada: Estudo do caso no Problema do Caixeiro Viajante}", booktitle = "{XXX SOBRAPO} - {Simp\'osio Brasileiro de Pesquisa Operacional, Curitiba, PR, Brasil, 25-27 de Novembro}", pages = "341--342", year ="1998", publisher = "{Sociedade Brasileira de Pesquisa Operacional}", note = "extended abstract" } @InProceedings{Buriol_Franca_Mendes_Moscato_98SOBRAPO, author = "P.M. {Fran\c{c}a} and P. Moscato and F. {M\"uller} and A.S. Mendes and L.S. Buriol", title = "{O Projeto MemePool: Um Framework para Otimiza\c{c}\~ao Combinat\'oria}", booktitle = "{XXX SOBRAPO} - {Simp\'osio Brasileiro de Pesquisa Operacional, Curitiba, PR, Brasil, 25-27 de Novembro}", pages = "20--21", year ="1998", publisher = "{Sociedade Brasileira de Pesquisa Operacional}", note = "extended abstract" } @InProceedings{Berretta_Moscato_98SOBRAPO, author = "R.E. Berretta and P. Moscato", title = "{Una an\'alise da utiliza\c{c}\ao de algoritmos gen\'eticos no problema de parti\c{c}\~ao de n\'umeros}", booktitle = "{XXX SOBRAPO} - {Simp\'osio Brasileiro de Pesquisa Operacional, Curitiba, PR, Brasil, 25-27 de Novembro}", pages = "271--272", year ="1998", publisher = "{Sociedade Brasileira de Pesquisa Operacional}", note = "extended abstract" } @InProceedings{Buriol_Franca_Moscato_99SOBRAPO, author = "L.S. Buriol and P.M. {Fran\c{c}a} and P. Moscato", title = "{Algoritmo Mem\'etico para o Problema do Caixeiro Viajante}", booktitle = "Proceedings of {XXXI SOBRAPO} - {Simp\'osio Brasileiro de Pesquisa Operacional, Juiz de Fora, MG, Brasil, 20-22 de Octobre}", pages = "1015--1028", year ="1999", publisher = "{Sociedade Brasileira de Pesquisa Operacional}" } @misc{Buriol_Franca_Moscato_Havana2000, title = "New heuristic results for the asymmetric traveling salesman problem", author = "L.S. Buriol and P.M. {Fran\c{c}a} and P. Moscato", note = "Abstract accepted to \emph{4th International Conference on Operations Research Optimization. Havana, March 6-10\/}. Organized by Universidad de La Habana and Humboldt-{Universit\"at} zu Berlin" } @misc{Buriol_Franca_Moscato_JOH99, title = "{A New Memetic Algorithm for the Asymmetric Traveling Salesman Problem}", author = "L.S. Buriol and P.M. Fran\c{c}a and P. Moscato", note = "Submitted to \emph{Journal of Heuristics\/} (October/1999), under revision" } @misc{Mendes_Franca_Moscato_ICANNGA2001, title = "{Fitness Landscapes for the Total Tardiness Single Machine Scheduling Problem}", author = "A.S. Mendes and P.M. Fran\c{c}a and P. Moscato", note = "Accepted at \emph{ICANNGA 2001 - V International Conference on Artificial Neural Networks and Genetic Algorithms, Prague, Czech Republic, April, 2001\/}" } @article{Franca_Mendes_MoscatoEJOR, title = "A Memetic Algorithm for the Total Tardiness Single Machine Scheduling Problem", author = "P.M. Fran\c{c}a and A.S. Mendes and P. Moscato", volume = "132", number = "1", pages = "224--242", year = "2001", ISSN = "03772217" } @article{Mendes_Muller_Franca_Moscato_2002, title = "Comparing Meta-Heuristic Approaches for Parallel Machine Scheduling Problems", author = "A.S. Mendes and F.M. M{\"u}ller and P.M. Fran\c{c}a and P. Moscato", journal = "Production Planning {\&} Control", volume = "13", number = "2", pages = "143--154", year = "2002", ISSN = "09537287" } @InProceedings{Mendes_Franca_Moscato_00fuzzy, author = "A.S. Mendes and P.M. {Fran\c{c}a} and P. Moscato", title = "{Fuzzy-Evolutionary Algorithms Applied to Scheduling Problems}", booktitle = "Proceedings of POM2000 - First World Conference on Production and Operations Management, Sevilla, Spain", pages = "1--10", year ="2000", publisher = "" } @InProceedings{Franca_Gupta_Mendes_Moscato_Veltink_99SOBRAPO, author = "P.M. Fran\c{c}a and J.D. Gupta and A.S. Mendes and P. and K.J. Veltink", title = "{Novos resultados para o problema de flowshop com fam\'{\i}lias de tarefas e tempos de prepara\c{c}\~ao}", booktitle = "Proceedings of {XXXI SOBRAPO} - {Simp\'osio Brasileiro de Pesquisa Operacional, Juiz de Fora, MG, Brasil, 20-22 de Octobre}", pages = "v.1., 394--401", year ="1999", publisher = "{Sociedade Brasileira de Pesquisa Operacional}" } @InProceedings{Franca_Gupta_Mendes_Moscato_Veltink_00flowshop, author = "P.M. Fran\c{c}a and J.D. Gupta and A.S. Mendes and P. Moscato and K.J. Veltink", title = "{Metaheuristic Approaches for the Pure Flowshop Manufacturing Cell Problem}", booktitle = "PMS2000 - 7th International Workshop On Project Management And Scheduling, Osnabr{\"u}ck, Germany", pages = "128--130", year ="2000", month = "April", publisher = "", note = "extended abstract" } @misc{Mendes_Franca_Moscato_IEEE, title = "On optimal instances and fitness landscapes for the Single Machine Scheduling Problem with sequence-dependent setup times", author = "A.S. Mendes and P.M. Fran\c{c}a and P. Moscato", note = "submitted to \emph{{IEEE} Transactions on Evolutionary Computation}" } @article{Mendes_Franca_Moscato_Landscapes2002, title = "Fitness Landscapes for the Total Tardiness Single Machine Scheduling Problem", author = "A.S. Mendes and P.M. Fran\c{c}a and P. Moscato", journal = "Neural Network World: an International Journal on Neural and Mass-Parallel Computing and Information Systems", year = "2002", ISSN = "1210-0552" } @Unpublished{Gockel:1997:lheavsr, author = "Nicole Gockel and Rolf Drechsler and Bernd Becker", title = "Learning Heuristics by Evolutionary Algorithms with Variable Size Representation", note = "Position paper at the Workshop on Evolutionary Computation with Variable Size Representation at ICGA-97", month = "20 " # jul, year = "1997", address = "East Lansing, MI, USA", keywords = "genetic algorithms, Evolvable Hardware, variable size representation", notes = "http://www.ai.mit.edu/people/unamay/icga-ws.html", size = "3 pages" } @article{Pal_93, author = "K.F. Pal", title = "Genetic algorithms for the traveling salesman problem based on a heuristic crossover operation", journal = "Biological Cybernetics", volume = "69", year = "1993", pages = "539--546" } @InProceedings{Pal_94, author = "K.F. Pal", title = "Selection schemes with spatial isolation for genetic optimization", booktitle = "Proceedings of the Third Conference on Parallel Problem Solving from Nature - PPSN III, Jerusalem, 1994", editor = "Y. Davidor and H.-P. Schwefel and R. Manner", series = "Lecture Notes in Computer Science", volume = "866", publisher = "Springer-Verlag", address = "Berlin, Germany", pages = "170--179", year = "1994" } @article{Pal_95, author = "K.F. Pal", title = "Genetic algorithms with local optimization", journal = "Biological Cybernetics", volume = "73", year = "1995", pages = "335--341" } @article{Pal_96a, author = "K.F. Pal", title = "The ground state energy of the Edwards-Anderson Ising spin glass with a hybrid genetic algorithm", journal = "Physica A", volume = "223", year = "1996", pages = "283--292" } @article{Pal_96b, author = "K.F. Pal", title = "The ground state energy of the cubic spin glass with short-range interactions of Gaussian distribution", journal = "Physica A", volume = "233", year = "1996", pages = "60--66" } @InProceedings(Kersting:2002:EvoWorkshops, author = "S. Kersting and G.R. Raidl and I. Ljubi\'c", title = "A Memetic Algorithm for Vertex-Biconnectivity Augmentation", booktitle = "Applications of Evolutionary Computing, Proceedings of EvoWorkshops2002: EvoCOP, EvoIASP, EvoSTim", year = "2002", editor = "S. Cagnoni and J. Gottlieb and E. Hart and M. Middendorf and G. Raidl", volume = "2279", series = {LNCS}, pages = "101--110", address = {Kinsale, Ireland}, publisher_address = {Berlin}, month = {3-4 April}, organisation ={EvoNet}, publisher = {Springer-Verlag}, note = {}, keywords = {evolutionary computation, applications}, ISBN = {}, url = {}, size = {10 pages}, abstract = {}, notes = {EvoWorkshops2002, part of cagnoni:2002:ews}, ) @InProceedings(Torres-Velazquez:2002:EvoWorkshops, author = "R. Torres-Vel\'{a}zquez and V. Estivill-Castro", title = "A Memetic Algorithm Guided by Quicksort for the Error-Correcting Graph Isomorphism Problem", booktitle = "Applications of Evolutionary Computing, Proceedings of EvoWorkshops2002: EvoCOP, EvoIASP, EvoSTim", year = "2002", editor = "S. Cagnoni and J. Gottlieb and E. Hart and M. Middendorf and G. Raidl", volume = {2279}, series = {LNCS}, pages = {171--180}, address = {Kinsale, Ireland}, publisher_address = {Berlin}, month = {3-4 April}, organisation ={EvoNet}, publisher = {Springer-Verlag}, note = {}, keywords = {evolutionary computation, applications}, ISBN = {}, url = {}, size = {10 pages}, abstract = {}, notes = {EvoWorkshops2002, part of cagnoni:2002:ews}, ) @InProceedings{Merz:2002:gecco, author = "P. Merz", title = "A Comparison Of Memetic Recombination Operators For The Traveling Salesman Problem", booktitle = "GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference", editor = "W. B. Langdon and E. Cant{\'u}-Paz and K. Mathias and R. Roy and D. Davis and R. Poli and K. Balakrishnan and V. Honavar and G. Rudolph and J. Wegener and L. Bull and M. A. Potter and A. C. Schultz and J. F. Miller and E. Burke and N. Jonoska", year = "2002", pages = "472--479", address = "New York", publisher_address = "San Francisco, CA 94104, USA", month = "9-13 July", publisher = "Morgan Kaufmann Publishers", keywords = "genetic algorithms", isbn = "1-55860-878-8", notes = "GECCO-2002. A joint meeting of the eleventh International Conference on Genetic Algorithms (ICGA-2002) and the seventh Annual Genetic Programming Conference (GP-2002)" } @InProceedings{Knodler:2002:gecco, author = "K. Kn{\"o}dler and J. Poland and A. Zell and A. Mitterer", title = "Memetic Algorithms For Combinatorial Optimization Problems In The Calibration Of Modern Combustion Engines", booktitle = "GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference", editor = "W. B. Langdon and E. Cant{\'u}-Paz and K. Mathias and R. Roy and D. Davis and R. Poli and K. Balakrishnan and V. Honavar and G. Rudolph and J. Wegener and L. Bull and M. A. Potter and A. C. Schultz and J. F. Miller and E. Burke and N. Jonoska", year = "2002", pages = "687", address = "New York", publisher_address = "San Francisco, CA 94104, USA", month = "9-13 July", publisher = "Morgan Kaufmann Publishers", keywords = "genetic algorithms, poster paper", isbn = "1-55860-878-8", notes = "GECCO-2002. A joint meeting of the eleventh International Conference on Genetic Algorithms (ICGA-2002) and the seventh Annual Genetic Programming Conference (GP-2002)" } @InProceedings{Roos:2002:gecco, author = "R.S. Roos and T. Bennett and J. Hannon and E. Zehner", title = "A Genetic Algorithm For Improved Shellsort Sequences", booktitle = "GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference", editor = "W. B. Langdon and E. Cant{\'u}-Paz and K. Mathias and R. Roy and D. Davis and R. Poli and K. Balakrishnan and V. Honavar and G. Rudolph and J. Wegener and L. Bull and M. A. Potter and A. C. Schultz and J. F. Miller and E. Burke and N. Jonoska", year = "2002", pages = "694", address = "New York", publisher_address = "San Francisco, CA 94104, USA", month = "9-13 July", publisher = "Morgan Kaufmann Publishers", keywords = "genetic algorithms, poster paper, memetic algorithm, noisy fitness function, shellsort", isbn = "1-55860-878-8", notes = "GECCO-2002. A joint meeting of the eleventh International Conference on Genetic Algorithms (ICGA-2002) and the seventh Annual Genetic Programming Conference (GP-2002)" } @InProceedings{gorges89a:ga, author = "{Martina Gorges-Schleuter}", title = "{ASPARAGOS}: An Asynchronous Parallel Genetic Optimization Strategy", booktitle = "Proceedings of the Third International Conference on Genetic Algorithms", editor = "J. David Schaffer", publisher = "Morgan Kaufmann Publishers", year = "1989" } @ARTICLE{105ieee, AUTHOR = "G. Rudolph", TITLE = "Global optimization by means of distributed evolution strategies", JOURNAL = "Parallel Problem solving from nature", YEAR = "1991", volume = "496", pages = "209--213" } @InProceedings{Carr:2002:gecco, author = "R. Carr and W. Hart and N. Krasnogor and J. Hirst and E. Burke and J. Smith", title = "Alignment Of Protein Structures With {A} Memetic Evolutionary Algorithm", booktitle = "GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference", editor = "W. B. Langdon and E. Cant{\'u}-Paz and K. Mathias and R. Roy and D. Davis and R. Poli and K. Balakrishnan and V. Honavar and G. Rudolph and J. Wegener and L. Bull and M. A. Potter and A. C. Schultz and J. F. Miller and E. Burke and N. Jonoska", year = "2002", pages = "1027--1034", address = "New York", publisher_address = "San Francisco, CA 94104, USA", month = "9-13 July", publisher = "Morgan Kaufmann Publishers", keywords = "real world applications", isbn = "1-55860-878-8", notes = "GECCO-2002. A joint meeting of the eleventh International Conference on Genetic Algorithms (ICGA-2002) and the seventh Annual Genetic Programming Conference (GP-2002)" } @InProceedings{krasnogor:2001:GECCO, title = "Emergence of Profitable Search Strategies Based on a Simple Inheritance Mechanism", author = "N. Krasnogor and J. Smith", pages = "432--439", year = "2001", publisher = {Morgan Kaufmann}, booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001)}, editor = "L. Spector and E.D. Goodman and A. Wu and W.B. Langdon and Hans-Michael Voigt and M. Gen and S. Sen and M. Dorigo and S. Pezeshk and M.H. Garzon and E. Burke", address = {San Francisco, California, USA}, publisher_address = {San Francisco, CA 94104, USA}, month = {7-11 July}, organisation ={}, note = {}, keywords = {genetic algorithms, Memetic Algorithms, Self-Adaptation, Phase Transitions, NK-Landscapes, TSP, OneMax}, ISBN = {1-55860-774-9}, url = {}, size = {}, abstract = {}, notes = {A joint meeting of the tenth International Conference on Genetic Algorithms (ICGA-2001) and the sixth Annual Genetic Programming Conference (GP-2001) Part of spector:2001:GECCO}, } @inproceedings(hart:2001:WMAW, author = "W.E. Hart and N. Krasnogor and J. Smith", title = "2nd Workshop on Memetic Algorithms: WOMA2001", booktitle = {Second Workshop on Memetic Algorithms (2nd WOMA)}, year = {2001}, editor = {W.E. Hart and N. Krasnogor and J. Smith}, pages = {138--139}, address = {San Francisco, California, USA}, month = {7 July}, note = {}, keywords = {}, url = {}, abstract = {}, notes = {GECCO-2001WKS Part of heckendorn:2001:GECCOWKS}, ) @inproceedings(areibi:2001:MAVPDII, author = "S. Areibi", title = "Memetic Algorithms for {VLSI} Physical Design: Implementation Issues", booktitle = "Second Workshop on Memetic Algorithms (2nd WOMA)", year = {2001}, editor = {W.E. Hart and N. Krasnogor and J. Smith}, pages = {140--145}, address = {San Francisco, California, USA}, month = {7 July}, note = {}, keywords = {}, url = {}, abstract = {}, notes = {GECCO-2001WKS Part of heckendorn:2001:GECCOWKS}, ) @inproceedings(hodgson:2001:MAATOCD, author = "R.J.W. Hodgson", title = "Memetic Algorithm Approach to Thin-Film Optical Coating Design", booktitle = {Second Workshop on Memetic Algorithms (2nd WOMA)}, year = {2001}, editor = {W.E. Hart and N. Krasnogor and J. Smith}, pages = {152--157}, address = {San Francisco, California, USA}, month = {7 July}, note = {}, keywords = {}, url = {}, abstract = {}, notes = {GECCO-2001WKS Part of heckendorn:2001:GECCOWKS}, ) @inproceedings(knowles:2001:ACAMECAMP, author = "J.D. Knowles and D.W. Corne", title = {A Comparative Assessment of Memetic, Evolutionary, and Constructive Algorithms for the Multiobjective {d-MST} Problem}, booktitle = {Second Workshop on Memetic Algorithms (2nd WOMA)}, year = {2001}, editor = {W.E. Hart and N. Krasnogor and J. Smith}, pages = {162--167}, address = {San Francisco, California, USA}, month = {7 July}, note = {}, keywords = {}, url = {}, abstract = {}, notes = {GECCO-2001WKS Part of heckendorn:2001:GECCOWKS}, ) @inproceedings(merz:2001:OPMACO, author = "P. Merz", title = "On the Performance of Memetic Algorithms in Combinatorial Optimization", booktitle = {Second Workshop on Memetic Algorithms (2nd WOMA)}, year = {2001}, editor = {W.E. Hart and N. Krasnogor and J. Smith}, pages = {168--173}, address = {San Francisco, California, USA}, month = {7 July}, note = {}, keywords = {}, url = {}, abstract = {}, notes = {GECCO-2001WKS Part of heckendorn:2001:GECCOWKS}, ) @InProceedings{Zelinka_MA:2001, author = "I. Zelinka and V. Vasek and K. Kolomaznik and P. Dostal and J. Lampinen", title = "Memetic algorithm and global optimization of chemical reactor", booktitle = "PC Control 2001, 13th International Conference on Process Control, High Tatras, Slovakia", year = "2001", URL = "http://iepc.vscht.cz/dnload/piepc.doc" } @InProceedings{Caorsi_2002, author = "S. Caorsi and A. Massa and M. Pastorino and M. Rafetto and A. Randazzo", title = "A new approach to microwave imaging based on a memetic algorithm", booktitle = "PIERS 2002, Progress in Electromagnetics Research Symposium July 1-4, 2002, Cambridge, Massachusetts, USA", URL ="http://ceta-mac1.mit.edu/piers2k2/abstracts/Caorsi.MPRR_BCM.pdf", year = "2002" } @InCollection{Poland_LNCS:2264, author = "J. Poland and K. {Kn\"odler} and A. Mitterer and T. Fleischhauer and F. Zuber-Goos and A. Zell", title = "Evolutionary Search for Smooth Maps in Motor Control Unit Calibration", editor = "Steinh{\"o}fel", booktitle = "Stochastic Algorithms: Foundations and Applications", pages = "107--116", publisher = "Springer-Verlag", series = "LNCS", volume = "2264", year = "2001", Abstract = "We study the combinatorial optimization task of choosing the smoothest map from a given family of maps, which is motivated from motor control unit calibration. The problem is of a particular interest because of its characteristics: it is NP-hard, it has a direct and important industrial application, it is easy-to-state and it shares some properties of the well-known Ising spin glass model. Moreover, it is appropriate for the application of randomized algorithms: for local search heuristics because its strong 2-dimensional local structure, and for Genetic Algorithms since there is a very natural and direct encoding which results in a variable alphabet. We present the problem from two points of view, an abstract view with a very simple definition of smoothness and the real-world application. We run local search, Genetic and Memetic Algorithms. We compare the direct encoding with unary and binary codings, and we try a 2-dimensional encoding. For a simple smoothness criterion, the Memetic Algorithm clearly performs best. However, if the smoothness citerion is more complex, the local search needs many function evaluations. Therefore we prefer the pure Genetic Algorithm for the application.", URL = "http://www.first.gmd.de/saga01/abstracts.html" } @InProceedings{Poland_Mitterer_Knodler_Zell_2001, author = "J. Poland and A. Mitterer and K. Knödler and A. Zell", title = "Memetic Algorithms Can Improve the Construction of {D}-Optimal Experimental Designs", editor = "N. Mastorakis", booktitle = "Advances In Fuzzy Systems and Evolutionary Computation", publisher = "World Scientific, Engineering Society Press: New York, Athens", pages = "227--231", year = "2001" } @InProceedings{Goncalves_OPT2001, title = "A Memetic Algorithm for the Examination Timetabling Problem", author = "Jos\'e Fernando Gon\c{c}alves", booktitle = "Optimization 2001, Aveiro, Portugal, July 23-25, 2001", URL ="http://www.mat.ua.pt/opt2001/pages/Presentation.asp?ID=111", abstract = "This paper presents a hybrid genetic algorithm for the Examination Timetabling Problem. The chromosome representation of the problem is based on random keys. The exams are schedule using a heuristic priority rule in which the priorities are defined by genetic algorithm. The approach is tested on a set random generated problems with known optimal solutions. The computation results validate the effectiveness of the proposed algorithm.", year = "2001" } % Project % Experimental Design Theoretic Directional Search: The Coupling Link of % Memetic Algorithm and Quality Engineering in Evolutionary Computing % http://www.ee.cityu.edu.hk/newweb/research/new_cerg.pdf @article{Quintero_Pierre_2001, title = "A Multi-population Memetic Algorithm to Optimize the Assignment of Cells to Switches in Cellular Mobile Networks", author = "A. Quintero and S. Pierre", journal = "", note = "submitted for publication", year = "2001", URL = "http://www.larim.polymtl.ca/samuel/pub.html" } @InProceedings{Merz_Freisleben_GeneExpression2002, author = "P. Merz and A. Zell", title = "Clustering Gene Expression Profiles with Memetic Algorithms", booktitle = "7th International Conference on Parallel Problem Solving from Nature - PPSN VII, September 7-11, 2002, Granada, Spain", year = "2002" } @article{Merz_Freisleben_JOH2002, author = "P. Merz and B. Freisleben", title = "Greedy and Local Search Heuristics for the Unconstrained Binary Quadratic Programming Problem", journal = "Journal of Heuristics", volume = "8", number = "2", pages = "197--213", year = "2002" } @BOOK{166ribeiro, AUTHOR = "M.J. Quinn", TITLE = "Parallel Computing: Theory and practice", PUBLISHER = "McGraw-Hill", YEAR = "1994" } @article{Merz_Freisleben_Complex_Systems, author = "P. Merz and B. Freisleben", title = "Memetic Algorithms for the Traveling Salesman Problem", journal = "Complex Systems", note = "to be published", year = "2002" } @article{Merz_Katayama_2002, author = "P. Merz and K. Katayama", title = "Memetic Algorithms for the Unconstrained Binary Quadratic Programming Problem", note = "to be published", journal = "Bio Systems", year = "2002", URL = "http://nari36a.ice.ous.ac.jp/~katayama/pub.html" } @InProceedings{Buriol_Resende_Ribeiro_2002, title = "A Memetic Algorithm for {OSPF} Routing", author = "L. Buriol and M.G.C. Resende and C.C. Ribeiro", booktitle = "Sixth {INFORMS} Telecommunications Conference, March 10-13, 2002 Hilton Deerfield Beach, Boca Raton, Florida", URL = "http://www.informs.org/Conf/Telecom02/Abstracts/Buriol01351173414.pdf", year = "2002" } @ARTICLE{163ribeiro, AUTHOR = "S.C. Porto, J.P. Kitajima and C.C. Ribeiro", TITLE = "A case study on parallel synchronous implementations of tabu search based on neighborhood decomposition", JOURNAL = "Investigacion Operativa", YEAR = "1996", volume = "5", pages = "207-223", } @Misc{137ribeiro, author = {T.G. Mattson}, title = {Scientific computation}, howpublished = {In parallel and distributed computing handbook }, year = {1996}, note = {Mc-Graw-Hill}, annote = {981--1002} } @InProceedings{Grefenstette89a, author = "John J. Grefenstette and James E. Baker", booktitle = "Proceedings of the Third International Conference on Genetic Algorithms", editor = "J. David Schaffer", publisher = "Morgan Kaufmann Publishers", title = "How Genetic Algorithms Work: {A} Critical Look at Implicit Parallelism", year = "1989" } @ARTICLE{calegari2, AUTHOR = "P. Calegari,D. Wagner and M. Pizarosso", TITLE = "Parallel Island-Based evolutionary Algorithm for Radio Network Design", JOURNAL = "Journal of Parallel and distributed Computing", YEAR = "1997", volume = "47", number = "1", pages = "86--90", month = "November" } @InProceedings{turton:1996:geog, author = "Turton and Openshaw and Diplock", title = "Some Geographic Applications of Genetic Programming on the Cray {T3D} Supercomputer", booktitle = "UK Parallel'96", year = "1996", editor = "Jesshope and Shafarenko", publisher = "Springer", keywords = "genetic algorithms, genetic programming", URL = "http://www.geog.leeds.ac.uk/staff/i.turton/ai/ukpar96.ps.Z", size = "16 pages", notes = "{"}REplacement of ephemeral constant by a parameter, the value of which is optimised using an embedded non-linar paramter estimation proceedure.{"} Spatial Interaction Modelling, Seattle, USA Subglacial Water System Case Study. Trapridge Glacier, Yukon. From messages to genetic-programming@cs.stanford.edu Tue, 03 Sep 1996 08:52:15 BST Thu, 05 Sep 1996 08:38:51 BST Basically we use an asyncronous steady state system which implicitly gives preferential treatment to faster evaluating models. Its written in F77 and MPI at the moment but RSN I will be reworking it as F90 with some more functionallity such as user configurable islands and such like. genetic-programming@cs.stanford.edu Tue, 10 Sep 1996 08:32:17 BST I have produced a program that converts s-experessions to infix equations that can be pasted into maple (or free equivalents, I'd guess) which has a simplify command. My code is at ftp://gam.leeds.ac.uk/pub/ian/pretoin.f", } @Misc{Fielder1993, AUTHOR = {D. Fielder and C. O. Alford}, TITLE = {Counting and Naming Connection Islands on a Grid of Conductors}, PAGES = {731--737}} @Misc{Hof91, author = "F. Hoffmeister", title = "Scalable Parallelism by Evolutionary Algorithms", pages = "175--198", year = "1991" } @InProceedings{Jog87a, author = "P. Jog and {Dirk Van Gucht}", booktitle = "Proceedings of the Second International Conference on Genetic Algorithms", editor = "John J. Grefenstette", publisher = "Lawrence Erlbaum Associates, Publishers", title = "Parallelisation of probabilistic sequential search algorithms", year = "1987" } @InProceedings{Robertson87a, author = "George G. Robertson", booktitle = "Proceedings of the Second International Conference on Genetic Algorithms", editor = "John J. Grefenstette", publisher = "Lawrence Erlbaum Associates, Publishers", title = "Parallel implementation of genetic algorithms in a classifier system", year = "1987" } @InProceedings{Pettey87a, author = "Chrisila B. Pettey and Michael R. Leuze and John J. Grefenstette", booktitle = "Proceedings of the Second International Conference on Genetic Algorithms", editor = "John J. Grefenstette", publisher = "Lawrence Erlbaum Associates, Publishers", title = "A parallel genetic algorithm", year = "1987", } @InProceedings{knight92a:ga, author = "L. R. Knight and R. L. Wainwright", publisher = "SPPCC'92", title = "{HYPERGEN}: {A} Distributed Genetic Algorithm on a Hypercube", booktitle = "Proceedings of the 1992 Scalable High Performance Computing Conference", year = "1992", } Added by Jason @InProceedings{Tanese87a, author = "R. Tanese", booktitle = "Proceedings of the Second International Conference on Genetic Algorithms", editor = "John J. Grefenstette", publisher = "Lawrence Erlbaum Associates, Publishers", title = "Parallel genetic algorithms for a hypercube", year = "1987" } @MISC{Adamidimikros, author = "P. Adamidis", title = "Review of parallel genetic algorithms bibliography", howpublished = "Tech. 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Furuhashi", series = "River Edge, NJ : World Scientific", pages = "349--356" } @PHDTHESIS{Martin2000, AUTHOR = "Martin Stuart Jones", TITLE = "An Object-Oriented Framework for the implementation of search techniques", SCHOOL = "School of Information Systems of the University of East Anglia", YEAR = "2000", type = "PhD Thesis", month = "February"} @INPROCEEDINGS{Lipsitch1991, CROSSREF = {Belew1991}, AUTHOR = {Marc Lipsitch}, TITLE = {Adaptation on Rugged Landscapes Generated by Iterated Local Interactions of Neighboring Memes}, PAGES = {128--135} } @Article{IEEE2002, author = {E. Alba and M. Tomassini}, title = {Parallelism and Evolutionary Algorithms}, journal = {IEEE Transactions on Evolutionary Computation}, year = {2002}, volume = {6}, number = {5}, pages = {443-448}, month = {October}} @Article{34, author = {M. Dorigo and L.M. 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