θ-PSO: a new strategy of particle swarm optimization

Particle swarm optimization (PSO) is an efficient, robust and simple optimization algorithm. Most studies are mainly concentrated on better understanding of the standard PSO control parameters, such as acceleration coefficients, etc. In this paper, a more simple strategy of PSO algorithm called θ-PS...

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Bibliographic Details
Published inJournal of Zhejiang University. A. Science Vol. 9; no. 6; pp. 786 - 790
Main Authors Wei-min, Zhong, Shao-jun, Li, Feng, Qian
Format Journal Article
LanguageEnglish
Published Hangzhou Zhejiang University Press 01.06.2008
State Key Laboratory of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China
Automation Institute, East China University of Science and Technology, Shanghai 200237, China
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Summary:Particle swarm optimization (PSO) is an efficient, robust and simple optimization algorithm. Most studies are mainly concentrated on better understanding of the standard PSO control parameters, such as acceleration coefficients, etc. In this paper, a more simple strategy of PSO algorithm called θ-PSO is proposed. In θ-PSO, an increment of phase angle vector replaces the increment of velocity vector and the positions are decided by the mapping of phase angles. Benchmark testing of nonlinear functions is described and the results show that the performance of θ-PSO is much more effective than that of the standard PSO.
Bibliography:TP301.6
Particle swarm optimization (PSO), Phase angle, Benchmark function
33-1236/O4
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:1673-565X
1862-1775
DOI:10.1631/jzus.A071278