New Particle Swarm Optimisation Algorithm with Hénon Chaotic Map Structure

A new Particle swarm optimisation(PSO)algorithm based on the H′enon chaotic map(hereafter HCPSO algorithm) is presented in this paper to deal with the premature convergence problem of the traditional PSO algorithm. The HCPSO algorithm changes the structure of the traditional PSO algorithm and deviat...

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Bibliographic Details
Published in电子学报：英文版 no. 4; pp. 747 - 753
Main Author YAN Tao LIU Fengxian CHEN Bin
Format Journal Article
LanguageEnglish
Published 2017
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Summary:A new Particle swarm optimisation(PSO)algorithm based on the H′enon chaotic map(hereafter HCPSO algorithm) is presented in this paper to deal with the premature convergence problem of the traditional PSO algorithm. The HCPSO algorithm changes the structure of the traditional PSO algorithm and deviates from the structures of conventional hybrid algorithms that merely introduce chaotic searching into PSO. Based on the convergence condition of PSO, the HCPSO algorithm can improve solution precision and increase the convergence rate by combing using the targeting technique of chaotic mapping. For validation, fourteen benchmark functions were used to compare the proposed algorithm with six other hybrid PSO algorithms. The experimental results indicated that the HCPSO algorithm is superior to the other algorithms in terms of convergence speed and solution accuracy.
Bibliography:YAN Tao;LIU Fengxian;CHEN Bin;Chengdu Institute of Computer Applications, Chinese Academy of Sciences;University of Chinese Academy of Sciences;Guangzhou Institute of Geochemistry, Chinese Academy of Sciencess;Guangzhou Institute of Electronic Technology, Chinese Academy of Sciences
10-1284/TN
ISSN:1022-4653