一种改进的粒子群优化算法  

An Improved Particle Swarm Optimization Algorithm

作　　者：张爱伟[1] 李金新[1] 

机构地区：[1]杭州电子科技大学电子信息学院,浙江杭州310018

出　　处：《杭州电子科技大学学报（自然科学版）》2016年第6期10-14,共5页Journal of Hangzhou Dianzi University：Natural Sciences

摘　　要：为解决标准粒子群优化算法收敛速度慢、容易陷入局部最优的问题,提出了一种基于标准粒子群优化算法的改进算法.通过对标准粒子群算法的速度和位置更新公式的修改,增强了粒子在搜索后期的多样性,提高了全局搜索能力,降低了陷入局部最优的可能性.用3个基准函数对改进算法进行验证,比较分析表明:NPSO与SPSO比,收敛速度明显提高,与可能出现不收敛的CFM比,一致收敛.In order to solve the problem of slow convergence and easy to fall into local optimum,an improved algorithm based on the standard particle swarm optimization algorithm is proposed.By modifying the velocity update formula and the position update formula of the standard particle swarm optimization algorithm,the diversity of the particle in the late period of search is improved,and the global searching ability is improved,and the possibility of falling into local optimum is reduced.3benchmark functions are used to validate the improved algorithm,and the results are compared with the other two particle swarm optimization algorithms.The experimental results show that the new algorithm has some improvement in the convergence rate and the local optimum.

关 键 词：粒子群算法 收敛速度 搜索能力 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]