论文信息 - Strategy Adaptation by Competing Subpopulations

Strategy Adaptation by Competing Subpopulations

The breeder genetic algorithm BGA depends on a set of con trol parameters and genetic operators In this paper it is shown that strategy adaptation by competing subpopulations makes the BGA more robust and more e cient Each subpopulation uses a di erent strategy which competes with other subpopulations Numerical results are pre sented for a number of test functions

Dirk Schlierkamp Voosen

[1] H. H. Rosenbrock,et al. An Automatic Method for Finding the Greatest or Least Value of a Function , 1960, Comput. J..

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

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

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

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

[6] Heinz Mühlenbein,et al. Predictive Models for the Breeder Genetic Algorithm I. Continuous Parameter Optimization , 1993, Evolutionary Computation.

[7] Heinz Mühlenbein,et al. The Science of Breeding and Its Application to the Breeder Genetic Algorithm (BGA) , 1993, Evolutionary Computation.

[8] Fabio Schoen,et al. A wide class of test functions for global optimization , 1993, J. Glob. Optim..

[9] Thomas Bäck,et al. An Overview of Evolutionary Algorithms for Parameter Optimization , 1993, Evolutionary Computation.