A genetic algorithm tutorial

This tutorial covers the canonical genetic algorithm as well as more experimental forms of genetic algorithms, including parallel island models and parallel cellular genetic algorithms. The tutorial also illustrates genetic search by hyperplane sampling. The theoretical foundations of genetic algorithms are reviewed, include the schema theorem as well as recently developed exact models of the canonical genetic algorithm.

[1]  James E. Baker,et al.  Reducing Bias and Inefficienry in the Selection Algorithm , 1987, ICGA.

[2]  Yuval Davidor,et al.  A Naturally Occurring Niche and Species Phenomenon: The Model and First Results , 1991, ICGA.

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

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

[5]  Gilbert Syswerda,et al.  A Study of Reproduction in Generational and Steady State Genetic Algorithms , 1990, FOGA.

[6]  W. Vent,et al.  Rechenberg, Ingo, Evolutionsstrategie — Optimierung technischer Systeme nach Prinzipien der biologischen Evolution. 170 S. mit 36 Abb. Frommann‐Holzboog‐Verlag. Stuttgart 1973. Broschiert , 1975 .

[7]  Reiko Tanese,et al.  Distributed Genetic Algorithms , 1989, ICGA.

[8]  D. E. Goldberg,et al.  Simple Genetic Algorithms and the Minimal, Deceptive Problem , 1987 .

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

[10]  L. Darrell Whitley,et al.  Fundamental Principles of Deception in Genetic Search , 1990, FOGA.

[11]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1992, Artificial Intelligence.

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

[13]  Heinz Mühlenbein,et al.  Evolution in Time and Space - The Parallel Genetic Algorithm , 1990, FOGA.

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

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

[16]  Kenneth A. De Jong,et al.  An Analysis of Multi-Point Crossover , 1990, FOGA.

[17]  Larry J. Eshelman The CHC Adaptive Search Algo-rithm , 1991 .

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

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

[20]  Michael D. Vose,et al.  Modeling Simple Genetic Algorithms , 1992, FOGA.

[21]  Thomas Bäck,et al.  A Survey of Evolution Strategies , 1991, ICGA.

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

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

[24]  Nils J. Nilsson,et al.  Artificial Intelligence , 1974, IFIP Congress.

[25]  Michael de la Maza,et al.  Book review: Genetic Algorithms + Data Structures = Evolution Programs by Zbigniew Michalewicz (Springer-Verlag, 1992) , 1993 .

[26]  Patrick Henry Winston,et al.  Artificial intelligence (3rd ed.) , 1992 .

[27]  D. Ackley A connectionist machine for genetic hillclimbing , 1987 .

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

[29]  John J. Grefenstette,et al.  How Genetic Algorithms Work: A Critical Look at Implicit Parallelism , 1989, ICGA.

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

[31]  Martina Gorges-Schleuter,et al.  Explicit Parallelism of Genetic Algorithms through Population Structures , 1990, PPSN.

[32]  L. Darrell Whitley,et al.  Optimization Using Distributed Genetic Algorithms , 1990, PPSN.

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

[34]  Hans-Paul Schwefel,et al.  Numerical Optimization of Computer Models , 1982 .

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

[36]  Lawrence Davis,et al.  Genetic Algorithms and Simulated Annealing , 1987 .

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

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

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

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

[41]  James E. Baker,et al.  Adaptive Selection Methods for Genetic Algorithms , 1985, International Conference on Genetic Algorithms.

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

[43]  L. Darrell Whitley,et al.  GENITOR II: a distributed genetic algorithm , 1990, J. Exp. Theor. Artif. Intell..

[44]  David E. Goldberg,et al.  An Analysis of Reproduction and Crossover in a Binary-Coded Genetic Algorithm , 1987, ICGA.

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

[46]  David E. Goldberg,et al.  A Note on Boltzmann Tournament Selection for Genetic Algorithms and Population-Oriented Simulated Annealing , 1990, Complex Syst..

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

[48]  Gunar E. Liepins,et al.  Punctuated Equilibria in Genetic Search , 1991, Complex Syst..

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

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