A Multi Sub-population Particle Swarm Optimizer Based on Clustering
基于聚类的多子群粒子群优化算法

On the basis of the particle swarm optimizer,A cluster-based particle swarm optimizer is proposed.In the proposed algorithm,the current particles is first divided into multi sub-population by clustering.Then,the current particles is updated by the personal best particle and gobal best particles in the sub-populations.The proposed algorithm exchanged and uses more particles' information,thus improves convergence performance.The experiment results demonstrate that the proposed algorithm is superior to original particle swarm optimization algorithm.