NDLI: Quantum-Behaved Particle Swarm Optimization with Cooperative-Competitive Coevolutionary

Content Provider	IEEE Xplore Digital Library
Author	Songfeng Lu Chengfu Sun
Copyright Year	2008
Description	Author affiliation: Huazhong Univ. of Sci. & Technol., Wuhan (Songfeng Lu; Chengfu Sun)
Abstract	Based on the previous introduced quantum-behaved particle swarm optimization (QPSO), in this paper, a revised QPSO with hybrid cooperative and competitive mechanism is proposed. The cooperative and competitive mechanism improves the diversity of the swarm, so as to help the system escape from local optima and converge to global optima. Take full advantages of the cooperative and competitive search among different swarms, cooperative competitive quantum-behaved particle swarm optimization (COQPSO) makes the swarms more efficient in global search. The experimental results on test functions show that COQPSO with cooperative and competitive mechanism outperforms the QPSO and even can search out the minimum value for some test functions.
Starting Page	593
Ending Page	597
File Size	233650
Page Count	5
File Format	PDF
ISBN	9780769534886
DOI	10.1109/KAM.2008.19
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Co-evolutionary Genetic mutations Educational institutions Probability distribution Particle swarm optimization Sun Cooperative-Competitive search Quantum computing Clustering algorithms Quantum mechanics Simulated annealing Quantum-behaved Particle Swarm Optimization Testing
Content Type	Text
Resource Type	Article

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