Operator and parameter adaptation in genetic algorithms
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[1] Ingo Rechenberg,et al. Evolutionsstrategie : Optimierung technischer Systeme nach Prinzipien der biologischen Evolution , 1973 .
[2] 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 .
[3] K. Dejong,et al. An analysis of the behavior of a class of genetic adaptive systems , 1975 .
[4] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .
[5] Kenneth Alan De Jong,et al. An analysis of the behavior of a class of genetic adaptive systems. , 1975 .
[6] H. P. Schwefel,et al. Numerische Optimierung von Computermodellen mittels der Evo-lutionsstrategie , 1977 .
[7] John J. Grefenstette,et al. Optimization of Control Parameters for Genetic Algorithms , 1986, IEEE Transactions on Systems, Man, and Cybernetics.
[8] J. David Schaffer,et al. An Adaptive Crossover Distribution Mechanism for Genetic Algorithms , 1987, ICGA.
[9] Darrell Whitley,et al. Genitor: a different genetic algorithm , 1988 .
[10] Rajarshi Das,et al. A Study of Control Parameters Affecting Online Performance of Genetic Algorithms for Function Optimization , 1989, ICGA.
[11] Terence C. Fogarty,et al. Varying the Probability of Mutation in the Genetic Algorithm , 1989, ICGA.
[12] Lawrence Davis,et al. Adapting Operator Probabilities in Genetic Algorithms , 1989, ICGA.
[13] Gilbert Syswerda,et al. Uniform Crossover in Genetic Algorithms , 1989, ICGA.
[14] Larry J. Eshelman,et al. Biases in the Crossover Landscape , 1989, ICGA.
[15] Kalyanmoy Deb,et al. Messy Genetic Algorithms: Motivation, Analysis, and First Results , 1989, Complex Syst..
[16] Kenneth A. De Jong,et al. An Analysis of the Interacting Roles of Population Size and Crossover in Genetic Algorithms , 1990, PPSN.
[17] Reinhard Männer,et al. Towards an Optimal Mutation Probability for Genetic Algorithms , 1990, PPSN.
[18] Larry J. Eshelman,et al. Preventing Premature Convergence in Genetic Algorithms by Preventing Incest , 1991, ICGA.
[19] Larry J. Eshelman,et al. On Crossover as an Evolutionarily Viable Strategy , 1991, ICGA.
[20] Thomas Bck,et al. Self-adaptation in genetic algorithms , 1991 .
[21] Yukinori Kakazu,et al. Adaptive Search Strategy for Genetic Algorithms with Additional Genetic Algorithms , 1992, PPSN.
[22] Robert E. Smith,et al. Adaptively Resizing Populations: An Algorithm and Analysis , 1993, ICGA.
[23] B. Freisleben,et al. Optimization of Genetic Algorithms by Genetic Algorithms , 1993 .
[24] John J. Grefenstette,et al. Genetic Algorithms for Tracking Changing Environments , 1993, ICGA.
[25] Hideyuki Takagi,et al. Dynamic Control of Genetic Algorithms Using Fuzzy Logic Techniques , 1993, ICGA.
[26] Zbigniew Michalewicz,et al. GAVaPS-a genetic algorithm with varying population size , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.
[27] Michèle Sebag,et al. Controlling Crossover through Inductive Learning , 1994, PPSN.
[28] Dirk Schlierkamp Voosen. Strategy Adaptation by Competing Subpopulations , 1994 .
[29] Peter Ross,et al. Fast Practical Evolutionary Timetabling , 1994, Evolutionary Computing, AISB Workshop.
[30] Heinz Mühlenbein,et al. Strategy Adaption by Competing Subpopulations , 1994, PPSN.
[31] Christian Bierwirth,et al. Control of Parallel Population Dynamics by Social-Like Behavior of GA-Individuals , 1994, PPSN.
[32] Lalit M. Patnaik,et al. Adaptive probabilities of crossover and mutation in genetic algorithms , 1994, IEEE Trans. Syst. Man Cybern..
[33] Peter J. Angeline,et al. Adaptive and Self-adaptive Evolutionary Computations , 1995 .
[34] William M. Spears,et al. Adapting Crossover in Evolutionary Algorithms , 1995, Evolutionary Programming.
[35] Bryant A. Julstrom,et al. What Have You Done for Me Lately? Adapting Operator Probabilities in a Steady-State Genetic Algorithm , 1995, ICGA.
[36] W. Spears,et al. On the Virtues of Parameterized Uniform Crossover , 1995 .
[37] Günter Rudolph,et al. A cellular genetic algorithm with self-adjusting acceptance threshold , 1995 .
[38] Robert E. Smith,et al. Adaptively Resizing Populations: Algorithm, Analysis, and First Results , 1993, Complex Syst..
[39] Jan Paredis,et al. The Symbiotic Evolution of Solutions and Their Representations , 1995, International Conference on Genetic Algorithms.
[40] Jim Smith,et al. An Adaptive Poly-Parental Recombination Strategy , 1995, Evolutionary Computing, AISB Workshop.
[41] James R. Levenick. Metabits: Generic Endogenous Crossover Control , 1995, ICGA.
[42] Jim Smith,et al. Recombination strategy adaptation via evolution of gene linkage , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.
[43] Joanna Lis,et al. Parallel genetic algorithm with the dynamic control parameter , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.
[44] Jim Smith,et al. Adaptively Parameterised Evolutionary Systems: Self-Adaptive Recombination and Mutation in a Genetic Algorithm , 1996, PPSN.
[45] Jim Smith,et al. Self adaptation of mutation rates in a steady state genetic algorithm , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.
[46] Zbigniew Michalewicz,et al. Self-Adaptive Genetic Algorithm for Numeric Functions , 1996, PPSN.
[47] Schloss Birlinghoven,et al. How Genetic Algorithms Really Work I.mutation and Hillclimbing , 2022 .