文章基本信息

标题：An Improved Algorithm of Quantum Particle Swarm Optimization
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作者：Jin,Jing Xue,Zhi-bin Shi, Yan-xia
期刊名称：Journal of Software
印刷版ISSN：1796-217X
出版年度：2014
卷号：9
期号：11
页码：2789-2795
DOI：10.4304/jsw.9.11.2789-2795
语种：English
出版社：Academy Publisher
摘要：Based on the classical particle optimization algorithm and the quantum behavioral theory, this paper proposes an improved QPSO algorithm---GLQPSO to perfect the global and local convergence speed ability and speed of classical particle swarm. To achieve this purpose, the author introduces an improved Logistic chaotic mapping theory [1] to conduct chaotic search for the initial particle and chaotic remolding of the locally optimized particle swarm. The test of the classical function has proved the success of this effort.
关键词：quantum behavior;PSO algorithm;chaotic mapping thoughts;local search