Evolutionary computation: comments on the history and current state

Evolutionary computation has started to receive significant attention during the last decade, although the origins can be traced back to the late 1950's. This article surveys the history as well as the current state of this rapidly growing field. We describe the purpose, the general structure, and the working principles of different approaches, including genetic algorithms (GA) (with links to genetic programming (GP) and classifier systems (CS)), evolution strategies (ES), and evolutionary programming (EP) by analysis and comparison of their most important constituents (i.e. representations, variation operators, reproduction, and selection mechanism). Finally, we give a brief overview on the manifold of application domains, although this necessarily must remain incomplete.

[1]  E. Thorndike.  On the Organization of Intellect. , 1921 .

[2]  Huebner,et al.  Proceedings of the First Annual Conference of the Wharton School of Finance and Commerce , 2022 .

[3]  Industrial Research , 1934, Nature.

[4]  George E. P. Box,et al.  Evolutionary Operation: a Method for Increasing Industrial Productivity , 1957 .

[5]  Richard M. Friedberg,et al.  A Learning Machine: Part I , 1958, IBM J. Res. Dev..

[6]  Richard M. Friedberg,et al.  A Learning Machine: Part II , 1959, IBM J. Res. Dev..

[7]  John H. Holland,et al.  Outline for a Logical Theory of Adaptive Systems , 1962, JACM.

[8]  Lawrence J. Fogel,et al.  Artificial Intelligence through Simulated Evolution , 1966 .

[9]  G. H. Burgin,et al.  On Playing Two-Person Zero-Sum Games against Nonminimax Players , 1969, IEEE Trans. Syst. Sci. Cybern..

[10]  Hans-Paul Schwefel,et al.  TWO-PHASE NOZZLE AND HOLLOW CORE JET EXPERIMENTS. , 1970 .

[11]  Ingo Rechenberg,et al.  Evolutionsstrategie : Optimierung technischer Systeme nach Prinzipien der biologischen Evolution , 1973 .

[12]  George H. Burgin,et al.  Systems Identification by Quasilinearization and by Evolutionary Programming , 1973 .

[13]  K. Dejong,et al.  An analysis of the behavior of a class of genetic adaptive systems , 1975 .

[14]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[15]  Kenneth Alan De Jong,et al.  An analysis of the behavior of a class of genetic adaptive systems. , 1975 .

[16]  J. W. Atmar,et al.  Speculation on the evolution of intelligence and its possible realization in machine form. , 1976 .

[17]  John H. Holland,et al.  Cognitive systems based on adaptive algorithms , 1977, SGAR.

[18]  H. P. Schwefel,et al.  Numerische Optimierung von Computermodellen mittels der Evo-lutionsstrategie , 1977 .

[19]  John H. Holland,et al.  COGNITIVE SYSTEMS BASED ON ADAPTIVE ALGORITHMS1 , 1978 .

[20]  Hans-Paul Schwefel,et al.  Direct search for optimal parameters within simulation models , 1979 .

[21]  Nichael Lynn Cramer,et al.  A Representation for the Adaptive Generation of Simple Sequential Programs , 1985, ICGA.

[22]  David E. Goldberg,et al.  Genetic Algorithms and Rules Learning in Dynamic System Control , 1985, ICGA.

[23]  J. E. Baker.  Adaptive Selection Methods for Genetic Algorithms , 1985, ICGA.

[24]  J. D. Schaffer,et al.  Multiple Objective Optimization with Vector Evaluated Genetic Algorithms , 1985, ICGA.

[25]  John J. Grefenstette,et al.  Optimization of Control Parameters for Genetic Algorithms , 1986, IEEE Transactions on Systems, Man, and Cybernetics.

[26]  Kenneth A. De Jong,et al.  On Using Genetic Algorithms to Search Program Spaces , 1987, ICGA.

[27]  J. David Schaffer,et al.  An Adaptive Crossover Distribution Mechanism for Genetic Algorithms , 1987, ICGA.

[28]  John H. Holland,et al.  Induction: Processes of Inference, Learning, and Discovery , 1987, IEEE Expert.

[29]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[30]  Darrell Whitley,et al.  Genitor: a different genetic algorithm , 1988 .

[31]  Rajarshi Das,et al.  A Study of Control Parameters Affecting Online Performance of Genetic Algorithms for Function Optimization , 1989, ICGA.

[32]  Rick L. Riolo,et al.  The Emergence of Default Hierarchies in Learning Classifier Systems , 1989, ICGA.

[33]  J. David Schaffer,et al.  Proceedings of the third international conference on Genetic algorithms , 1989 .

[34]  Terence C. Fogarty,et al.  Varying the Probability of Mutation in the Genetic Algorithm , 1989, ICGA.

[35]  Gilbert Syswerda,et al.  Uniform Crossover in Genetic Algorithms , 1989, ICGA.

[36]  Martina Gorges-Schleuter,et al.  ASPARAGOS An Asynchronous Parallel Genetic Optimization Strategy , 1989, ICGA.

[37]  Aimo A. Törn,et al.  Global Optimization , 1999, Science.

[38]  D.E. Goldberg,et al.  Classifier Systems and Genetic Algorithms , 1989, Artif. Intell..

[39]  L. Darrell Whitley,et al.  The GENITOR Algorithm and Selection Pressure: Why Rank-Based Allocation of Reproductive Trials is Best , 1989, ICGA.

[40]  Larry J. Eshelman,et al.  Biases in the Crossover Landscape , 1989, ICGA.

[41]  Bernard Manderick,et al.  Fine-Grained Parallel Genetic Algorithms , 1989, ICGA.

[42]  Jim Antonisse,et al.  A New Interpretation of Schema Notation that Overtums the Binary Encoding Constraint , 1989, ICGA.

[43]  Kalyanmoy Deb,et al.  Messy Genetic Algorithms: Motivation, Analysis, and First Results , 1989, Complex Syst..

[44]  Rick L. Riolo,et al.  The Emergence of Coupled Sequences of Classifiers , 1989, ICGA.

[45]  John R. Koza,et al.  Hierarchical Genetic Algorithms Operating on Populations of Computer Programs , 1989, IJCAI.

[46]  L. Darrell Whitley,et al.  Genetic algorithms and neural networks: optimizing connections and connectivity , 1990, Parallel Comput..

[47]  John J. Grefenstette,et al.  Conditions for Implicit Parallelism , 1990, FOGA.

[48]  David E. Goldberg,et al.  The Theory of Virtual Alphabets , 1990, PPSN.

[49]  Günter Rudolph,et al.  Global Optimization by Means of Distributed Evolution Strategies , 1990, PPSN.

[50]  Lawrence. Davis,et al.  Handbook Of Genetic Algorithms , 1990 .

[51]  Stephanie Forrest,et al.  Emergent computation: self-organizing, collective, and cooperative phenomena in natural and artificial computing networks , 1990 .

[52]  Frank Kursawe,et al.  A Variant of Evolution Strategies for Vector Optimization , 1990, PPSN.

[53]  Alden H. Wright,et al.  Genetic Algorithms for Real Parameter Optimization , 1990, FOGA.

[54]  John J. Grefenstette,et al.  Explanations of Empirically Derived Reactive Plans , 1990, ML.

[55]  W. Daniel Hillis,et al.  Co-evolving parasites improve simulated evolution as an optimization procedure , 1990 .

[56]  Jonathan Schull,et al.  The View from the Adaptive Landscape , 1990, Parallel Problem Solving from Nature.

[57]  Roberto Serra,et al.  Complex Systems and Cognitive Processes , 1990, Springer Berlin Heidelberg.

[58]  Kalyanmoy Deb,et al.  A Comparative Analysis of Selection Schemes Used in Genetic Algorithms , 1990, FOGA.

[59]  Charles L. Karr,et al.  Genetic algorithms for fuzzy controllers , 1991 .

[60]  Lashon B. Booker,et al.  Proceedings of the fourth international conference on Genetic algorithms , 1991 .

[61]  Frank Hoffmeister,et al.  Scalable Parallelism by Evolutionary Algorithms , 1991 .

[62]  Stuart A. Kauffman,et al.  The origins of order , 1993 .

[63]  Zbigniew Michalewicz,et al.  An Experimental Comparison of Binary and Floating Point Representations in Genetic Algorithms , 1991, ICGA.

[64]  Nicholas J. Radcliffe,et al.  Equivalence Class Analysis of Genetic Algorithms , 1991, Complex Syst..

[65]  David R. Jefferson,et al.  Selection in Massively Parallel Genetic Algorithms , 1991, ICGA.

[66]  David B. Fogel,et al.  Meta-evolutionary programming , 1991, [1991] Conference Record of the Twenty-Fifth Asilomar Conference on Signals, Systems & Computers.

[67]  Thomas Bck,et al.  Self-adaptation in genetic algorithms , 1991 .

[68]  Philip R. Thrift,et al.  Fuzzy Logic Synthesis with Genetic Algorithms , 1991, ICGA.

[69]  Abdollah Homaifar,et al.  Full design of fuzzy controllers using genetic algorithms , 1992, Optics & Photonics.

[70]  Kalyanmoy Deb,et al.  Genetic Algorithms, Noise, and the Sizing of Populations , 1992, Complex Syst..

[71]  L. Darrell Whitley,et al.  An Executable Model of a Simple Genetic Algorithm , 1992, FOGA.

[72]  Reinhard Männer,et al.  Parallel Problem Solving from Nature 2, PPSN-II, Brussels, Belgium, September 28-30, 1992 , 1992, Parallel Problem Solving from Nature.

[73]  D. P. Kwok,et al.  Optimal fuzzy PID control based on genetic algorithm , 1992, Proceedings of the 1992 International Conference on Industrial Electronics, Control, Instrumentation, and Automation.

[74]  Kenneth A. De Jong,et al.  Generation Gaps Revisited , 1992, FOGA.

[75]  Kennetb A. De.  Genetic Algorithms Are NOT Function Optimizers , 1992 .

[76]  Kenneth A. De Jong,et al.  Are Genetic Algorithms Function Optimizers? , 1992, PPSN.

[77]  Michael Herdy,et al.  Reproductive Isolation as Strategy Parameter in Hierarichally Organized Evolution Strategies , 1992, PPSN.

[78]  J. D. Schaffer,et al.  Real-Coded Genetic Algorithms and Interval-Schemata , 1992, FOGA.

[79]  Günter Rudolph,et al.  On Correlated Mutations in Evolution Strategies , 1992, PPSN.

[80]  Adam P. Arkin,et al.  Recursive Ensemble Mutagenesis: A Combinatorial Optimization Technique for Protein Engineering , 1992, PPSN.

[81]  Martina Gorges-Schleuter,et al.  Comparison of Local Mating Strategies in Massively Parallel Genetic Algorithms , 1992, PPSN.

[82]  Andreas Ostermeier,et al.  An Evolution Strategy with Momentum Adaptation of the Random Number Distribution , 1992, PPSN.

[83]  Hans-Georg Beyer,et al.  Some Aspects of the 'Evolution Strategiy' for Solving TSP-Like Optimization Problems Appearing at the Design Studies of a 0.5 TeV e+e--Linear Collider , 1992, Parallel Problem Solving from Nature.

[84]  Kenneth A. De Jong,et al.  Genetic Algorithms are NOT Function Optimizers , 1992, FOGA.

[85]  Heinz Mühlenbein,et al.  How Genetic Algorithms Really Work: Mutation and Hillclimbing , 1992, PPSN.

[86]  John J. Grefenstette,et al.  Deception Considered Harmful , 1992, FOGA.

[87]  F. G. Pin,et al.  Mobile manipulator configuration optimization using evolutionary programming , 1992 .

[88]  Shumeet Baluja,et al.  Structure and Performance of Fine-Grain Parallelism in Genetic Search , 1993, ICGA.

[89]  Masayuki Yanagiya,et al.  A Simple Mutation-Dependent Genetic Algorithm , 1993, ICGA.

[90]  Larry J. Eshelman,et al.  Foundations of Genetic Algorithms-2 , 1993 .

[91]  C. L. Karr,et al.  Fuzzy control of pH using genetic algorithms , 1993, IEEE Trans. Fuzzy Syst..

[92]  Joachim Stender,et al.  Parallel Genetic Algorithms: Introduction and Overview of Current Research , 1993 .

[93]  Peter J. Angeline,et al.  Competitive Environments Evolve Better Solutions for Complex Tasks , 1993, ICGA.

[94]  L. Darrell Whitley,et al.  Cellular Genetic Algorithms , 1993, ICGA.

[95]  Thomas Bäck,et al.  Optimal Mutation Rates in Genetic Search , 1993, ICGA.

[96]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[97]  Larry J. Eshelman,et al.  Designing Multiplierless Digital Filters Using Genetic Algorithms , 1993, ICGA.

[98]  Peter Ross,et al.  A Promising Genetic Algorithm Approach to Job-Shop SchedulingRe-Schedulingand Open-Shop Scheduling Problems , 1993, ICGA.

[99]  Roger L. Wainwright,et al.  Multiple Vehicle Routing with Time and Capacity Constraints Using Genetic Algorithms , 1993, ICGA.

[100]  Steffen Schulze-Kremer,et al.  Genetic Algorithms for Protein Tertiary Structure Prediction , 1993, ECML.

[101]  J. C. Bean.  Genetics and random keys for sequencing amd optimization , 1993 .

[102]  Larry J. Eshelman,et al.  Crossover's Niche , 1993, ICGA.

[103]  Ron Unger,et al.  Genetic Algorithm for 3D Protein Folding Simulations , 1993, ICGA.

[104]  Masaharu Munetomo,et al.  An Efficient Migration Scheme for Subpopulation-Based Asynchronously Parallel Genetic Algorithms , 1993, ICGA.

[105]  Lawrence Davis,et al.  A Genetic Algorithm for Survivable Network Design , 1993, International Conference on Genetic Algorithms.

[106]  Kalyanmoy Deb,et al.  RapidAccurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms , 1993, ICGA.

[107]  W. C. Page,et al.  Configuration Optimization of Mobile Manipulators With Equality Constraints Using Evolutionary Programming , 1993 .

[108]  Kate Juliff,et al.  A Multi-chromosome Genetic Algorithm for Pallet Loading , 1993, International Conference on Genetic Algorithms.

[109]  Martin Mandischer,et al.  Representation and Evolution of Neural Networks , 1993 .

[110]  Zbigniew Michalewicz,et al.  A Hierarchy of Evolution Programs: An Experimental Study , 1993, Evolutionary Computation.

[111]  L. J. Eshelman,et al.  chapter Real-Coded Genetic Algorithms and Interval-Schemata , 1993 .

[112]  Ralf Bruns,et al.  Direct Chromosome Representation and Advanced Genetic Operators for Production Scheduling , 1993, ICGA.

[113]  Frédéric Gruau,et al.  Genetic Synthesis of Modular Neural Networks , 1993, ICGA.

[114]  Lawrence J. Fogel,et al.  Proceedings of the Third Annual Conference on Evolutionary Programming, 24-26 Feb 94, San Diego, California, USA , 1994 .

[115]  A. E. Eiben,et al.  Genetic algorithms with multi-parent recombination , 1994, PPSN.

[116]  L. Darrell Whitley,et al.  Cellular genetic algorithms as function optimizers: locality effects , 1994, SAC '94.

[117]  Thomas Bäck,et al.  An evolutionary approach to combinatorial optimization problems , 1994, CSC '94.

[118]  Gordon I. McCalla,et al.  TEN YEARS OF COMPUTATIONAL INTELLIGENCE , 1994 .

[119]  Hans-Georg Beyer,et al.  Toward a Theory of Evolution Strategies: The (, )-Theory , 1994, Evolutionary Computation.

[120]  Larry J. Eshelman,et al.  Productive Recombination and Propagating and Preserving Schemata , 1994, FOGA.

[121]  Wirt Atmar,et al.  Notes on the simulation of evolution , 1994, IEEE Trans. Neural Networks.

[122]  L. Darrell Whitley,et al.  A note on the performance of genetic algorithms on zero-one knapsack problems , 1994, SAC '94.

[123]  Reinhard Männer,et al.  Parallel Problem Solving from Nature — PPSN III , 1994, Lecture Notes in Computer Science.

[124]  N. Hansen,et al.  Step-Size Adaptation Based on Non-Local Use Selection Information , 1994 .

[125]  Nikolaus Hansen,et al.  Step-Size Adaption Based on Non-Local Use of Selection Information , 1994, PPSN.

[126]  Kenneth A. De Jong,et al.  Using Markov Chains to Analyze GAFOs , 1994, FOGA.

[127]  Melanie Mitchell,et al.  Genetic Algorithms and Artificial Life , 1994, Artificial Life.

[128]  Una-May O'Reilly,et al.  The Troubling Aspects of a Building Block Hypothesis for Genetic Programming , 1994, FOGA.

[129]  Alden H. Wright,et al.  Simple Genetic Algorithms with Linear Fitness , 1994, Evolutionary Computation.

[130]  David B. Fogel,et al.  Evolving neurocontrollers using evolutionary programming , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[131]  Reinhard Männer,et al.  Parallel problem solving from nature--PPSN III : International Conference on Evolutionary Computation, the Third Conference on Parallel Problem Solving from Nature, Jerusalem, Israel, October 9-14, 1994 : proceedings , 1994 .

[132]  Günter Rudolph,et al.  Convergence analysis of canonical genetic algorithms , 1994, IEEE Trans. Neural Networks.

[133]  Patrick D. Surry,et al.  Fitness Variance of Formae and Performance Prediction , 1994, FOGA.

[134]  L. Altenberg.  The evolution of evolvability in genetic programming , 1994 .

[135]  Anne L. Olsen.  Penalty functions and the knapsack problem , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[136]  Stewart W. Wilson.  ZCS: A Zeroth Level Classifier System , 1994, Evolutionary Computation.

[137]  Günter Rudolph,et al.  An Evolutionary Algorithm for Integer Programming , 1994, PPSN.

[138]  E. W. Haasdijk,et al.  Sex between models-inductive modelling using genetic algorithms , 1994 .

[139]  Thomas Bäck,et al.  Selective Pressure in Evolutionary Algorithms: A Characterization of Selection Mechanisms , 1994, International Conference on Evolutionary Computation.

[140]  Ingo Rechenberg,et al.  Evolutionsstrategie '94 , 1994, Werkstatt Bionik und Evolutionstechnik.

[141]  L. Booker.  Foundations of genetic algorithms. 2: L. Darrell Whitley (Ed.), Morgan Kaufmann, San Mateo, CA, 1993, ISBN 1-55860-263-1, 322 pp., US$45.95 , 1994 .

[142]  Peter J. Angeline,et al.  An evolutionary algorithm that constructs recurrent neural networks , 1994, IEEE Trans. Neural Networks.

[143]  J. K. Kinnear,et al.  Advances in Genetic Programming , 1994 .

[144]  William M. Spears,et al.  Adapting Crossover in Evolutionary Algorithms , 1995, Evolutionary Programming.

[145]  Russell W. Anderson.  Genetic Mechanisms Underlying the Baldwin Effect Are Evident in Natural Antibodies , 1995, Evolutionary Programming.

[146]  Larry R. Medsker,et al.  Genetic Algorithms and Neural Networks , 1995 .

[147]  Hans-Georg Beyer,et al.  Toward a Theory of Evolution Strategies: On the Benefits of Sex the (/, ) Theory , 1995, Evolutionary Computation.

[148]  Suran Asitha Goonatilake,et al.  Intelligent Systems for Finance and Business , 1995 .

[149]  Günter Rudolph,et al.  A cellular genetic algorithm with self-adjusting acceptance threshold , 1995 .

[150]  A. E. Eiben,et al.  Orgy in the Computer: Multi-Parent Reproduction in Genetic Algorithms , 1995, ECAL.

[151]  F. Kursawe,et al.  Towards self-adapting evolution strategies , 1995, Proceedings of 1995 IEEE International Conference on Evolutionary Computation.

[152]  Jarmo T. Alander,et al.  An Indexed Bibliography of Genetic Algorithms , 1995 .

[153]  Robert G. Reynolds,et al.  Evolutionary Programming IV: Proceedings of the Fourth Annual Conference on Evolutionary Programming , 1995 .

[154]  Edmund M. A. Ronald,et al.  When Selection Meets Seduction , 1995, ICGA.

[155]  Michael D. Vose,et al.  Modeling Simple Genetic Algorithms , 1995, Evolutionary Computation.

[156]  Hans-Paul Schwefel,et al.  Evolution and optimum seeking , 1995, Sixth-generation computer technology series.

[157]  Günter Rudolph,et al.  Contemporary Evolution Strategies , 1995, ECAL.

[158]  David B. Fogel,et al.  Evolutionary Computation: Towards a New Philosophy of Machine Intelligence , 1995 .

[159]  Peter J. Fleming,et al.  An Overview of Evolutionary Algorithms in Multiobjective Optimization , 1995, Evolutionary Computation.

[160]  SchoolImperial CollegeLondon.  A Genetic Algorithm for the Set Partitioning Problem , 1995 .

[161]  Hans-Georg Beyer,et al.  Toward a Theory of Evolution Strategies: Self-Adaptation , 1995, Evolutionary Computation.

[162]  D. Fogel,et al.  A comparison of methods for self-adaptation in evolutionary algorithms. , 1995, Bio Systems.

[163]  Joe Suzuki,et al.  A Markov chain analysis on simple genetic algorithms , 1995, IEEE Trans. Syst. Man Cybern..

[164]  Patrick D. Surry,et al.  Formal Algorithms + Formal Representations = Search Strategies , 1996, PPSN.

[165]  Jean-Michel Renders,et al.  Hybrid methods using genetic algorithms for global optimization , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[166]  W. Banzhaf,et al.  Genetic programming using genotype-phenotype mapping from linear genomes into linear phenotypes , 1996 .

[167]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.

[168]  Thomas Bäck,et al.  Evolutionary computation: an overview , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[169]  Thomas Bäck,et al.  Evolutionary Algorithms in Theory and Practice , 1996 .

[170]  Ulrich Hammel,et al.  Optimization of Heat Exchanger Networks by Means of Evolution Strategies , 1996, PPSN.

[171]  Zbigniew Michalewicz,et al.  A Note on Usefulness of Geometrical Crossover for Numerical Optimization Problems , 1996, Evolutionary Programming.

[172]  Paul G. Harrald,et al.  Evolutionary Algorithms and Economic Models: A View , 1996, Evolutionary Programming.

[173]  Zbigniew Michalewicz,et al.  Evolutionary Algorithms for Constrained Parameter Optimization Problems , 1996, Evolutionary Computation.

[174]  David B. Fogel,et al.  Tuning Evolutionary Programming for Conformationally Flexible Molecular Docking , 1996, Evolutionary Programming.

[175]  Peter J. Angeline,et al.  The Effects of Noise on Self-Adaptive Evolutionary Optimization , 1996, Evolutionary Programming.

[176]  Martin Schütz,et al.  Application of Parallel Mixed-Integer Evolution Strategies with Mutation Rate Pooling , 1996, Evolutionary Programming.

[177]  Thomas Bäck,et al.  Intelligent Mutation Rate Control in Canonical Genetic Algorithms , 1996, ISMIS.

[178]  Proceedings of the Fifth Annual Conference on Evolutionary Programming, EP 1996, San Diego, CA, USA, February 29 - March 2, 1996 , 1996 .

[179]  Peter Nordin,et al.  Benchmarking the generalization capabilities of a compiling genetic programming system using sparse data sets , 1996 .

[180]  Jim Smith,et al.  Self adaptation of mutation rates in a steady state genetic algorithm , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[181]  Jan Paredis,et al.  Coevolutionary Life-Time Learning , 1996, PPSN.

[182]  Cornelia Kappler,et al.  Evolutionary algorithms support refueling of pressurized water reactors , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[183]  Dorothea Heiss-Czedik,et al.  An Introduction to Genetic Algorithms. , 1997, Artificial Life.

[184]  David B. Fogel,et al.  Evolutionary algorithms in theory and practice , 1997, Complex.

[185]  Jeffrey Horn,et al.  Handbook of evolutionary computation , 1997 .

[186]  A. Eiben,et al.  A multi-sexual genetic algorithm for multiobjective optimization , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[187]  Thomas Bäck,et al.  Evolutionary computation: Toward a new philosophy of machine intelligence , 1997, Complex..

[188]  Georges R. Harik,et al.  Foundations of Genetic Algorithms , 1997 .

[189]  M. A. Stuchly,et al.  Electromagnetic System Design Using Genetic Algorithms , 1999 .

[190]  Schloss Birlinghoven,et al.  How Genetic Algorithms Really Work I.mutation and Hillclimbing , 2022 .

[191]  B. Kappen.  Minimizing the System Error in Feedforward Neural Networks with Evolution Strategy , 2022 .