文献类型：期刊文献

英文题名：A dynamic inertia weight particle swarm optimization algorithm

作者：Jiao, Bin[1,2];Lian, Zhigang[1];Gu, Xingsheng[1]

机构：[1]E China Univ Sci & Technol, Res Inst Automat, Shanghai 200237, Peoples R China;[2]Shanghai DianJi Univ, Dept Elect Engn, Shanghai 200240, Peoples R China

年份：2008

卷号：37

期号：3

起止页码：698

外文期刊名：CHAOS SOLITONS & FRACTALS

收录：;EI(收录号：20081111143038);WOS:【SCI-EXPANDED(收录号:WOS:000255084800009)】；

语种：英文

外文关键词：Algorithms - Benchmarking - Dynamic models - Functional analysis

摘要：Particle swarm optimization (PSO) algorithm has been developing rapidly and has been applied widely since it was introduced, as it is easily understood and realized. This paper presents an improved particle swarm optimization algorithm (IPSO) to improve the performance of standard PSO, which uses the dynamic inertia weight that decreases according to iterative generation increasing. It is tested with a set of 6 benchmark functions with 30, 50 and 150 different dimensions and compared with standard PSO. Experimental results indicate that the IPSO improves the search performance on the benchmark functions significantly. (c) 2006 Elsevier Ltd. All rights reserved.