Presentation 2013-05-27
Dynamics of Particle Swarm Optimization and Its Network Structure
Kenya JIN'NO,
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Abstract(in English) This article analyzes the convergence property of the particle swarm optimization. The inter-particle communication of the particle swarm optimization is realized by the past history of the neighbors and depends on the network structure of the swarm. We focus on an average path length of the network, and we clarify the relationship between the average path length and its searching performance. The result indicates that a long average path length is effective for multi-modal functions and multi-optima problems. Moreover, we define an index that means the variance of the personal best of each particle. We measure a diversity of the PSO system by using this index. The simulation results indicate that the network topology with long path length has the diversity.
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Keyword(in English) particle swarm optimization / network structure / variance / diversity / average path length / multi-modal function / multi-optima problem
Paper # NLP2013-12
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Conference Information
Committee NLP
Conference Date 2013/5/20(1days)
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Paper Information
Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Dynamics of Particle Swarm Optimization and Its Network Structure
Sub Title (in English)
Keyword(1) particle swarm optimization
Keyword(2) network structure
Keyword(3) variance
Keyword(4) diversity
Keyword(5) average path length
Keyword(6) multi-modal function
Keyword(7) multi-optima problem
1st Author's Name Kenya JIN'NO
1st Author's Affiliation EEE Dept., Nippon Institute of Technology()
Date 2013-05-27
Paper # NLP2013-12
Volume (vol) vol.113
Number (no) 69
Page pp.pp.-
#Pages 4
Date of Issue