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论文类型：期刊论文

发表时间：2012-07-01

发表刊物：Journal of Computational Information Systems

收录刊物：EI、Scopus

卷号：8

期号：13

页面范围：5401-5408

摘要：This paper proposed a modulo-similarity model based on fitness values and distances between different particles. This model can cluster particles with great similarity into several sub-swarms. We proposed a new adaptively multimodal particle swarm optimization algorithm based on this new similarity model. The proposed method doesn't rely on any prespecified niching parameter. Experiments show that MMPSO has comparable or better performance than rpso in handling a set of standard multimodal test functions. Moreover, MMPSO needs lower computation cost than rpso. ? 2011 by Binary Information Press.