摘要
Genetic algorithm is a widely used optimization method. Crossover and mutation are two Basicl operatorsof the genetic algorithm. On the basis of analyzing the principles of simple genetic algorithm and discussing its exist-ing problems of crossover point and mutation bit, this paper presents a way of the adaptive multiple bit mutation ge-netic algorithm , which not only can keep the population diversity but also has quicker convergence speed. The resultsof the multi-modal function optimization show that the adaptive multiple bit mutation genetic algorithm is practicaland efficient.
Genetic algorithm is a widely used optimization method. Crossover and mutation are two Basicl operators of the genetic algorithm. On the basis of analyzing the principles of simple genetic algorithm and discussing its existing problems of crossover point and mutation bit, this paper presents a way of the adaptive multiple bit mutation genetic algorithm , which not only can keep the population diversity but also has quicker convergence speed. The results of the multi-modal function optimization show that the adaptive multiple bit mutation genetic algorithm is practical and efficient.
出处
《计算机科学》
CSCD
北大核心
2003年第8期141-143,共3页
Computer Science
关键词
自适应多位变异遗传算法
搜索算法
搜索性能
随机数
Adaptive multiple bit mutation genetic algorithm, Crossover probability, Mutation probability, Convergence property
