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《Journal of Jilin University(Information Science Edition)》 2006-02
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New Particle-Swarm-Optimization Algorithm

CHEN Yong-gang,YANG Feng-jie,SUN Ji-gui (College of Computer Science and Technology,Jilin University,Changchun 130012,China)  
PSO(Particle Swarm Optimization) is an efficient stochastic global optimization technique.PSO algorithm will get struck at local optima easily.For the drawback,two aspects of improvements are proposed.One is that it gives the new definition of global extreme value in original pso algorithms velocity update formula.The Main function is to make the particles keep variety.The other is that it enlarges or shrinks fitness value properly,which,combined with random rule,determines a certain particle as global extreme value in speed update formula.NPSO(New PSO) forms afer above two aspects of imprevemnets are used in running later stage of pso algorithm.It can avoid getting struck at local optima effectively.The experiment results demonstrate that proposed algorithm is superior to original PSO algorithm obviously.Three test functions are selected.The mean fitness value obtained by using NPSO is about from 1.62% to 16.5% highter than that obtained by using pso algorithm under given conditions.
【Fund】: 国家自然科学基金资助项目(60273080 60473003);; 吉林省科技发展基金资助项目(20040526);; 吉林省杰出青年基金资助项目(20030107)
【CateGory Index】: TP301.6
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