关键词: 文化算法, 高斯变异, 粒子群算法

Abstract: Particle Swarm Optimization（PSO） is a new heuristic global optimization algorithm based on swarm intelligence.The algorithm is simple，easy to implement and has good performance of optimization.Now it has been applied in many fields.However，when optimizing multidimensional and multimodal functions，the basic particle swarm optimization is apt to be trapped in local optimum.Combing with cultural algorithm and Gaussian mutation，an improved particle swarms cooperative optimization algorithm is presented.This modified version can break away from the attraction of the local optimal solution.Simulation results on benchmark complex functions with high dimension show that this algorithm performs better than the basic particle swarms cooperative optimization algorithm.

Key words: cultural algorithm, Gaussian mutation, Particle Swarm Optimization（PSO）