Cooperative particle swarm optimization algorithm base on fuzzy migratory operator

In this article, a cooperative particle swarm optimization is proposed to increase the diversity of the swarm to avoid the drawback of trapping in a local optimum. Besides, a migratory operator on the basis of comprehensive fuzzy evaluation is employed to control the distribution of particles during iterations. The experimental results conducted on three benchmark functions show the performances of the proposed method are superior to that of classical PSO and particle swarm cooperative optimizer.