计算机工程2011，Vol.37Issue(22)：185-186,190,3.
基于混沌局部搜索的双种群遗传算法
Dual Population Genetic Algorithm Based on Chaotic Local Search
张晓伟1
作者信息
- 1. 广东工程职业技术学院计算机信息系,广州511363
- 折叠
摘要
Abstract
Dual population genetic algorithm with chaotic local search strategy is proposed to solve bad local search ability and early convergence which are the two defects of genetic algorithm. In proposed algorithm, one population is used as exploration population, the other is exploitation population. The two populations are evolved by different crossover probability and mutation probability. At the end of each generation, chaotic local search is applied to the optimal solution of each population, and the solution will be the new optimal solution if a solution found by chaotic local search is better than the optimal solution. Chaotic local search is not stopped until the predefined search time is elapsed. An immigration operation is down between the two populations each ten generation. Experimental results on six benchmark functions show that proposed algorithm had the better ability of finding optimal solution.关键词
混沌搜索/局部搜索/早熟收敛/双种群遗传算法/函数优化Key words
chaoic search/ local search/ premature convergence/ dual population genetic algorithm/ function optimization分类
信息技术与安全科学引用本文复制引用
张晓伟..基于混沌局部搜索的双种群遗传算法[J].计算机工程,2011,37(22):185-186,190,3.
