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粒子群算法中惯性权重的实验与分析
引用本文:王俊伟,汪定伟.粒子群算法中惯性权重的实验与分析[J].系统工程学报,2005,20(2):194-198.
作者姓名:王俊伟  汪定伟
作者单位:东北大学信息科学与工程学院,辽宁,沈阳,110004
基金项目:国家自然科学基金重点资助项目(70431003).
摘    要:简要介绍了粒子群算法(PSO),对算法中的重要参数惯性权重进行了系统的实验,分析了固定权重与时变权重的选择问题,并从问题依赖性、种群大小和拓扑结构等方面详细分析了惯性权重对于算法性能的影响.结果表明,惯性权重的问题依赖性较小,随着种群的增大,其取值应适当减小,局部版本下,惯性权重的选择具有更大的自由度.

关 键 词:粒子群算法  进化计算  惯性权重
文章编号:1000-5781(2005)02-0194-05

Experiments and analysis on inertia weight in particle swarm optimization
WANG Jun-wei,WANG Ding-wei.Experiments and analysis on inertia weight in particle swarm optimization[J].Journal of Systems Engineering,2005,20(2):194-198.
Authors:WANG Jun-wei  WANG Ding-wei
Abstract:The basic principle of particle swarm optimization (PSO) is introduced briefly in the paper. Sufficient experiments are done on inertia weight that is an important parameter in the algorithm. The selection difference between fixed and time-variant inertia weight is analyzed. And the influence of inertia weight on the algorithm performance is analyzed in detail from different aspects, including the problem dependence, swarm size and topologic structure. The result indicates the inertia weight has little problem dependence, and with the increase of the population its value should decrease properly. The selection of inertia weight has more freedom in the local version of PSO.
Keywords:particle swarm optimization  evolutionary computation  inertia weight
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