计算机科学
計算機科學
계산궤과학
COMPUTER SCIENCE
2003年
8期
141-143
,共3页
Adaptive multiple bit mutation genetic algorithm%Crossover probability%Mutation probability%Conver-gence property
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.
