A Particle Swarm Optimization with Variety Factor

Hai Sheng Qin; Deng Yue Wei; Jun Hui Li; Lei Zhang; Yan Qiang Feng

doi:10.4028/www.scientific.net/AMM.239-240.1291

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 239-240A Particle Swarm Optimization with Variety Factor

A Particle Swarm Optimization with Variety Factor

Abstract:

A new particle swarm optimization (PSO) algorithm (a PSO with Variety Factor, VFPSO) based on the PSO was proposed. Compared with the previous algorithm, the proposed algorithm is to update the Variety Factor and to improve the inertia weight of the PSO. The target of the improvement is that the new algorithm could go on enhancing the robustness as before and should reduce the risk of premature convergence. The simulation experiments show that it has great advantages of convergence property over some other modified PSO algorithms, and also avoids algorithm being trapped in local minimum effectively. So it can avoid the phenomenon of premature convergence.

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Periodical:

Applied Mechanics and Materials (Volumes 239-240)

Pages:

1291-1297

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.239-240.1291

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Online since:

December 2012

Authors:

Hai Sheng Qin, Deng Yue Wei, Jun Hui Li, Lei Zhang, Yan Qiang Feng

Keywords:

Inertia Weight, Particle Swarm Optimization (PSO), Premature Convergence, Variety Factor

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