The particle swarm optimization algorithm: convergence analysis and parameter selection

被引：1889

作者：

Trelea, IC ^{[1
]}

机构：

[1] INA PG, UMR Genie & Microbiol Proc Alimentaires, F-78850 Thiverval Grignon, France

来源：

INFORMATION PROCESSING LETTERS | 2003年 / 85卷 / 06期

关键词：

particle swarm optimization; stochastic optimization; analysis of algorithms; parallel algorithms;

D O I：

10.1016/S0020-0190(02)00447-7

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The particle swarm optimization algorithm is analyzed using standard results from the dynamic system theory. Graphical parameter selection guidelines are derived. The exploration-exploitation tradeoff is discussed and illustrated. Examples of performance on benchmark functions superior to previously published results are given. (C) 2002 Elsevier Science B.V. All rights reserved.

引用

页码：317 / 325

页数：9

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Clerc, M ;

Kennedy, J .

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[2]

Clerc M., 2002, Proceedings of the 1999 Congress on Evolutionary Computation, DOI DOI 10.1109/CEC.1999.785513

[3]

Eberhart RC, 2000, IEEE C EVOL COMPUTAT, P84, DOI 10.1109/CEC.2000.870279

[4]

Kennedy J, 1995, 1995 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS PROCEEDINGS, VOLS 1-6, P1942, DOI 10.1109/icnn.1995.488968

[5]

Kennedy J., 2001, SWARM INTELLIGENCE

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