Abstract: Particle swarm optimization algorithm is a stochastic global optimization technique. It has been successfully applied in many areas. PSO algorithm can be implemented with ease and few parameters need to be tuned. Based on the study on the principles of traditional PSO, mutation operator has been presented during the searching process in order to prevent from getting into the local optimum. The improved algorithm is applied to optimize several functions. The simulation results show its feasibility and validity.

Key words: Particle swarm optimization algorithm, mutation operator, optimization

摘要： 粒子群算法是一种随机全局优化算法，由于算法简单易于实现、可调参数少等特点，已得到了广泛的研究和应用。本文在研究标准算法原理的基础上，在算法搜索过程中引入变异算子，克服标准算法易陷入局部极优点的不足。将改进后的算法运用常见的几个测试函数进行了寻优仿真，仿真结果验证了带变异算子的粒子群算法的可行性和有效性。

关键词: 粒子群算法, 变异算子, 优化