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CLC number: TP301.6
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
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θ-PSO: a new strategy of particle swarm optimization
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Wei-min ZHONG, Shao-jun LI, Feng QIAN. θ-PSO: a new strategy of particle swarm optimization[J]. Journal of Zhejiang University Science A, 2008, 9(6): 786-790.
@article{title="θ-PSO: a new strategy of particle swarm optimization",
author="Wei-min ZHONG, Shao-jun LI, Feng QIAN",
journal="Journal of Zhejiang University Science A",
volume="9",
number="6",
pages="786-790",
year="2008",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A071278"
}
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A071278
TY - JOUR
T1 - θ-PSO: a new strategy of particle swarm optimization
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A1 - Shao-jun LI
A1 - Feng QIAN
J0 - Journal of Zhejiang University Science A
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EP - 790
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.A071278
Abstract: 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.
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