Volume 9 Number 11 (Nov. 2014)
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JSW 2014 Vol.9(11): 2789-2795 ISSN: 1796-217X
doi: 10.4304/jsw.9.11.2789-2795

An Improved Algorithm of Quantum Particle Swarm Optimization

Yan-xia JIN, Jing XUE, Zhi-bin SHI
North University of China/Department of Computer Science and Technology, Taiyuan, China
Abstract—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.

Index Terms—Terms—quantum behavior, PSO algorithm, chaotic mapping thoughts, local search

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Cite: Yan-xia JIN, Jing XUE, Zhi-bin SHI, "An Improved Algorithm of Quantum Particle Swarm Optimization," Journal of Software vol. 9, no. 11, pp. 2789-2795, 2014.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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