关键词: 粒子群优化, 群体智能, 惯性权重, 压缩因子, 局部极值, 全局极值

Abstract: An Enhanced Particle Swarm Optimization (EPSO) algorithm was proposed to overcome the disadvantage of PSO such as easily falling into local optimal at the latter part of the evolution. In this algorithm, when particle fell into local extremum point, the algorithm enhanced its ability of searching global optimal value by enhancing the particle's self-study ability, the other relative particles' ability of exploring new search space and the information communication in particles. The experimental results indicate that the new method has good ability of searching optimal value.

Key words: Particle Swarm Optimization (PSO), swarm intelligence, inertia weight, constriction factor, local extremum, global extremum