论文信息 - Characterizing crossover in genetic algorithms

Characterizing crossover in genetic algorithms

We characterize crossover and schemata; crossover is a binary operator that preserves schemata and commutes with addition and projection. Moreover, for any setS of chromosomes and familyF of crossover operators, we fully characterize the reachable chromosomes.

Gunar E. Liepins | Michael D. Vose | M. Vose | G. Liepins

[1] A. E. Eiben,et al. Global Convergence of Genetic Algorithms: A Markov Chain Analysis , 1990, PPSN.

[2] D. E. Goldberg,et al. Genetic Algorithms in Search , 1989 .

[3] Kalyanmoy Deb,et al. Messy Genetic Algorithms Revisited: Studies in Mixed Size and Scale , 1990, Complex Syst..

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

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

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

[7] Larry J. Eshelman,et al. The CHC Adaptive Search Algorithm: How to Have Safe Search When Engaging in Nontraditional Genetic Recombination , 1990, FOGA.

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

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

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

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

[12] Gunar E. Liepins,et al. Global convergence of genetic algorithms , 1992, Optics & Photonics.