Improved distributed genetic algorithm with cooperative-competitive genetic operators
Hernan E. Aguirre, Kiyoshi Tanaka, Tatsuo Sugimura, Shinjiro Oshita · 2002
We have presented an empirical model of genetic algorithms (GA) that puts parallel genetic operators in a cooperative-competitive stand with each other. An improved GA (GA-SRM) based on this model remarkably improves the search performance of a single population GA. We extend GA-SRM to distributed GAs in order to improve the performance of multiple population GAs. Simulation results verify that the parallel genetic operators in GA-SRM, CM and SRM, can successfully contribute to improve the search performance of distributed GAs.