计算机应用研究2013，Vol.30Issue(8)：2273-2275,3.DOI:10.3969/j.issn.1001-3695.2013.08.008
一种求解复杂多峰问题的新型粒子群优化算法研究
Novel particle swarm optimizer for solving complicated multimodal problem
摘要
Abstract
In order to deal with the problems of the slow convergence and easily converging to local optima,this paper proposed a classification learning PSO based on hyperspherical coordinates.It presented the method of determination of poor performance particle,and divided the swarm into three parts where introduced three learning strategies to improve the swarm to escape from local optima.Additionally,to decrease outside disturbance,it updated the particle positions and velocities in hyperspherical coordinate system,which improved the probability flying to the optimal solution.It conducted the simulation experi ments of three typical functions,and the results show the effectiveness of the proposed algorithm compared with other algorithms.Consequently,CLPSO-HC can be used as an effective algorithm to solve complex multimodal problems.关键词
粒子群优化/多峰问题/笛卡尔坐标/球形坐标Key words
particle swarm optimizer(PSO) / multimodal problem/ Cartesian coordinate/ hyperspherical coordinates分类
信息技术与安全科学引用本文复制引用
高钦翔,刘衍民..一种求解复杂多峰问题的新型粒子群优化算法研究[J].计算机应用研究,2013,30(8):2273-2275,3.基金项目
中国博士后基金资助项目(2012M520936) （2012M520936）
上海市博士后基金资助项目(12R21416000) （12R21416000）
贵州省科学技术基金资助项目(黔科合J字LKZS[2012]01号,[2012]2340号,LKZS[2012]10号) （黔科合J字LKZS[2012]01号,[2012]2340号,LKZS[2012]10号）
遵义师范学院博士基金资助项目(2012BSJJ19) （2012BSJJ19）
遵义师范学院基础教育研究课题(13ZYJ007) （13ZYJ007）
贵州省高校优秀科技创新人才支持计划基金资助项目(黔教合KY[2012]104号) （黔教合KY[2012]104号）
