An Improved Brain Storm Optimization with Learning Strategy

摘要

Brain Storm Optimization (BSO) algorithm is a brand-new and promising swarm intelligence algorithm by mimicking human being's behavior of brainstorming. This paper presents an improved BSO, i.e., BSO with learning strategy (BSOLS). It utilizes a novel learning strategy whereby the first half individuals with better fitness values maintain their superiority by keeping away from the worst ones while other individuals with worse fitness values improve their performances by learning from the excellent ones. The improved algorithm is tested on 10 classical benchmark functions. Comparative experimental results illustrate that the proposed algorithm performs significantly better than the original BSO and standard particle swarm optimization algorithm.