在对一种保证全局收敛的微粒群算法——随机PSO算法(SPSO)进行分析的基础上,提出了一种基于聚类分析的随机微粒群算法(CSPSO)。CSPSO算法保证了种群的多样性,使微粒能够有效地进行全局搜索。并证明了它依概率收敛于全局最优解。最后以典型的复杂基准优化问题进行了仿真实验,验证了CSPSO的有效性。
A new Stochastic Particle Swarm Optimization algorithm based on Cluster analysis (CSPSO) is proposed based on the analysis of Stochastic Particle Swarm Optimization algorithm (SPSO) that guarantees global convergence.The CSPSO is guaranteed that the particles are diversiform,and can make particles explore the global optimization more efficiently.The CSPSO is guaranteed to converge to the global optimization solution with probability one.Finally,several complex examples are simulated to show that CSPSO is more efficient than SPSO.