重庆理工大学学报：自然科学2012，Vol.26Issue(6)：67-70,4.
分阶段进化的粒子群优化算法
A New Particle Swarm Multi-stages Optimization Algorithm
摘要
Abstract
In view of the shortcomings of the standard particle swarm optimization algorithm （PSO） easily falling into local optimization when solving multi-extreme value function, a multi-stages optimi- zation algorithm is presented through analyzing the evolution principle and the reason of premature convergence in this paper. The improved algorithm divides the evolution process into multi-stages. In addition, a different fit iterative formula is adopted in each stage, so the population diversity can be increased and the premature convergence ean be effectively avoided accordingly. Simulation results show that the improved algorithm has better global extreme function problems optimization capability than standard PSO on multi-关键词
粒子群优化算法/局部最优/种群多样性Key words
particle swarm optimization algorithm/local optimization/population diversity分类
信息技术与安全科学引用本文复制引用
吴文欢,张少辉,李巍,吴烈阳,刘圣卿..分阶段进化的粒子群优化算法[J].重庆理工大学学报：自然科学,2012,26(6):67-70,4.基金项目
国家自然科学基金资助项目 （）
航空科学基金资助项目 （）
周口师范学院青年科研基金资助项目 （）
