中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
An Improved Particle Swarm Optimization Based on Self-Adaptive Escape Velocity

文献类型:期刊论文

作者Ran He(赫然); Yongji Wang; Qing Wang; Jinhui Zhou
刊名Chinese Journal of Software
出版日期2005
卷号16期号:12页码:2036-2044
关键词Particle Swarm Optimization Escape Velocity Self-adaptive Mutation Swarm Intelligence
英文摘要To deal with the problem of premature convergence and slow search speed, this paper proposes a novel particle swarm optimization (PSO) called self-adaptive escape PSO, which is guaranteed to converge to the global optimization solution with probability one. Considering that the organisms have the phenomena of escaping from the original cradle when they find the survival density is too high to live, this paper uses a special mutation –escape operator to make particles explore the search space more efficiently. The novel strategy produces a large speed value dynamically according to the variation of the speed, which makes the algorithm explore the local and global minima thoroughly at the same time. Experimental simulations show that the proposed method can not only significantly speed up the convergence, but also effectively solve the premature convergence problem .
源URL[http://ir.ia.ac.cn/handle/173211/21081]  
专题自动化研究所_09年以前成果
推荐引用方式
GB/T 7714
Ran He,Yongji Wang,Qing Wang,et al. An Improved Particle Swarm Optimization Based on Self-Adaptive Escape Velocity[J]. Chinese Journal of Software,2005,16(12):2036-2044.
APA Ran He,Yongji Wang,Qing Wang,&Jinhui Zhou.(2005).An Improved Particle Swarm Optimization Based on Self-Adaptive Escape Velocity.Chinese Journal of Software,16(12),2036-2044.
MLA Ran He,et al."An Improved Particle Swarm Optimization Based on Self-Adaptive Escape Velocity".Chinese Journal of Software 16.12(2005):2036-2044.

入库方式: OAI收割

来源:自动化研究所

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