关键词: 遗传算法, 多峰函数优化, 适应值共享, 自适应参数调整, 模糊相似聚类

Abstract: Determining the count of niche and the value of niche radius is a hard problem for multiple hump functions，so the niche genetic algorithm based on fuzzy similarity clustering and self-adaptive controlling of peaks radii is proposed.The basic idea of the method is that，in the process of genetic evolvement，it takes the radii of peaks as a part of optimization variables，the radii of peaks are coded，put in the chromosomes and optimized with the variables of the problem by fitness sharing genetic algorithm without a prior knowledge of the above parameters；In the process of clustering，it controls the number of converged niches through adjusting the fuzzy similarity degree，avoiding finding the invalid extreme points as well.Theoretical analysis and numerical experiments indicate that the algorithm takes no need to know the concrete number of niches and the value of the niche radium in advance，having a good searching ability on various multiple hump functions.

Key words: genetic algorithm, multiple hump function optimization, fitness sharing, self-adaptive parameter control, fuzzy similarity clustering