关键词: 粒子群优化, 早熟收敛, 区域震荡搜索, 全局优化

Abstract: To solve the premature convergence problem of the Particle Swarm Optimization（PSO）, an improved PSO algorithm is proposed. On the basis of attractor of each particle in the particle swarm, region shock search factor is embedded in the new algorithm. During converging cooperatively, each particle searches the surrounding area of particle extremum position, increasing the diversity of the population, enhancing the ability of global optimization of the algorithm and avoiding algorithm to fall into local convergence effectively. The simulation results show that the improved algorithm gets a significant improvement in convergence accuracy.

Key words: Particle Swarm Optimization（PSO）, premature convergence, regional shock search, global optimization