关键词: 粒子群优化算法, 变异算子, 自适应惯性权重, 全局优化

Abstract: A modified Particle Swarm Optimization（PSO） is proposed to improve the performance of standard PSO that is easily trapped in local optimum and has a slow convergence rate in the late period.On the basis of standard PSO，the modified algorithm applies some methods such as citing a nonlinearly descending inertia，changing the velocity iteration formula and introducing the mutation operator during the running time.The experimental results show that the new algorithm has great advantage of convergence property over standard PSO.

Key words: Particle Swarm Optimization（PSO）, mutation operator, adaptive inertia weight, global optimization