Quantum-Behaved Particle Swarm Optimization with Chaotic Search

Kaiqiao YANG  Hirosato NOMURA  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E91-D   No.7   pp.1963-1970
Publication Date: 2008/07/01
Online ISSN: 1745-1361
DOI: 10.1093/ietisy/e91-d.7.1963
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Algorithm Theory
Keyword: 
PSO,  QPSO,  chaotic search,  

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Summary: 
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.