A Niching Genetic Algorithm Based on Clustering and Resource Competition

A standard genetic algorithm only has the capability of converging to a single peak point eventually for a multimodal function optimization problem An improved GA used niche mechanism can gain a set of local peak A new niching GA based on clustering and resource competition is approved Clustering, a sharing model, and a crowd method are organized in this algorithm A multimodal function can be optimized efficiently by it without determining the count of niche and the value of niche radius It is proved by mathematics analysis that the number of converged peak can be controlled so as to avoid the inefficient points These conclusions are approved by the test of a typical problem