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改进的PSO混合算法
引用本文:杨恢先,刘子文,汪俊,王绪四,谢鹏鹤.改进的PSO混合算法[J].计算机应用,2010,30(6):1516-1518.
作者姓名:杨恢先  刘子文  汪俊  王绪四  谢鹏鹤
作者单位:1. 湖南湘潭大学材料与光电物理学院2. 湘潭大学信息工程学院3. 4. 湘潭大学材料与光电物理学院
基金项目:海南省自然科学基金资助项目(60897)
摘    要:为了提高粒子群算法的寻优速度和寻优精度,提出一种改进的PSO混合算法。在差分进化(DE)算法中引入了动态比例因子,在PSO算法中引入DE算法的变异、交叉操作,重新构造PSO算法的粒子位置更新公式。选取了4个基准函数进行测试,并与其他PSO混合算法作了比较。仿真结果表明该方法是有效的。

关 键 词:粒子群算法    差分进化算法    变异    交叉
收稿时间:2009-12-23
修稿时间:2010-03-07

Modified PSO hybrid algorithm
YANG Hui-xian,LIU Zi-wen,WANG Jun,WANG Xu-si,XIE Peng-he.Modified PSO hybrid algorithm[J].journal of Computer Applications,2010,30(6):1516-1518.
Authors:YANG Hui-xian  LIU Zi-wen  WANG Jun  WANG Xu-si  XIE Peng-he
Affiliation:1.Faculty of Materials/a>;Optoelectronics and Physics/a>;Xiangtan University/a>;Xiangtan Hunan 411105/a>;China/a>;2.College of Information Engineering/a>;China
Abstract:This paper proposed a novel Particle Swarm Optimization (PSO) hybrid algorithm to improve the optimum speed and performance of the PSO algorithm.This new algorithm introduced a dynamic proportion operator into differential evolution algorithm and also introduced mutation,crossover operator from DE algorithm into PSO algorithm.Then the position updating formula of PSO was reconstructed.At last,this paper chose four reference functions to have a test and compared the results with other PSO hybrid algorithms.T...
Keywords:PSO algorithm                                                                                                                        differential evolution algorithm                                                                                                                        mutation                                                                                                                        crossover
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