关键词: 遗传算法, 多染色体交叉, 小生境算法, 实数编码

Abstract: Mating of biological evolution generally occurs only between two individuals, and crossover operation of the traditional genetic algorithm is also carried out between two chromosomes. In the paper, the crossover operator is carried out on three or more chromosomes and the corresponding crossover operator is designed. Multi-Chromosomes Crossover Operator（MCCO） can significantly improve the optimization ability and convergence rate, but it is easy to produce premature convergence due to the fast convergence speed. Therefore, a niche algorithm with the sub population elimination tactics is designed in order to avoid the phenomenon of premature convergence. Compared with the experimental results of several genetic algorithms, it is proven that the MCCO genetic algorithm is better than the traditional genetic algorithm in the multi-apices optimization.

Key words: genetic algorithm, Multi-Chromosomes Crossover Operator（MCCO）, niche algorithm, real coded