摘要
针对目前多模态优化存在无法找到全部局部极值解的问题,提出了一种改进的小生境遗传算法.该算法在基于淘汰相似机制的小生境遗传算法中引入了预选择机制,并对自适应交叉概率算子和变异概率算子进行了改进,根据群体适应度值的大小来动态调整个体的交叉概率和变异概率大小,并将该算法用于Shubert函数的求解,实验结果表明该方法较之前的小生境遗传算法能够有效的搜寻出全部局部极值,并具有较快的搜索速度.同时,该方法在其他的多峰函数求解上具有通用性.
This paper presents an improved niche genetic algorithm applied to multimodal function optimization for finding all the extreme solutions. This algorithm is pre-selected niche based and similarity based on the mechanism of eliminating the niche combination. We improve the adaptive crossover operator and mutation operator according to the probability, crossover probability and mutation probability the fitness value to dynamically adjust the individual. And the algorithm is usecl to solve a typical multi peak, the experimental results show that the niche genetic algorithmcan searchall themultimodal functions＇ optimal solutions and extreme solutions, and has faster search speed. At the same time, this method is universal in the multi peak function for the other.
出处
《计算机系统应用》
2014年第10期101-106,共6页
Computer Systems & Applications
关键词
多模态
优化
小生境遗传算法
预选择
淘汰相似机制
multi modal
optimization
niche genetic algorithrn （NGA）
pre-seleeted
mechanismof eliminating the similarn
