Quantum-behaved particle swarm optimization with chaotic search

被引：11
|
作者：
Yang, Kaiqiao [1 ]
Nomura, Hirosato [1 ]
机构：
[1] Kyushu Inst Technol, Fac Comp Sci & Syst Engn, Iizuka, Fukuoka 8208502, Japan
来源：
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS | 2008年 / E91D卷 / 07期
关键词：
PSO; QPSO; chaotic search;
D O I：
10.1093/ietisy/e91-d.7.1963
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The chaotic search is introduced into Quantum-behaved Particle Swarm Optimization (QPSO) to increase the diversity of the swarm in the latter period of the search, so as to help the system escape from local optima. Taking full advantages of the characteristics of ergodicity and randomicity of chaotic variables, the chaotic search is carried out in the neighborhoods of the particles which are trapped into local optima. The experimental results on test functions show that QPSO with chaotic search outperforms the Particle Swarm Optimization (PSO) and QPSO.
引用
收藏
页码：1963 / 1970
页数：8
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