A new golden ratio local search based particle swarm optimization

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Sun, Yanxia, Van Wyk, Barend Jacobus, Wang, Zenghui. IEEE; 2012. A new golden ratio local search based particle swarm optimization.

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Please use this identifier to cite or link to this item: http://hdl.handle.net/10210/21329

Title: A new golden ratio local search based particle swarm optimization
Creator: Sun, Yanxia
Creator: Van Wyk, Barend Jacobus
Creator: Wang, Zenghui
Subject: Particle swarm optimization
Subject: Golden ratio
Subject: Local search
Date: 2012
Publisher: IEEE
Description: Abstract: At beginning of the search process of particle swarm optimization, one of the disadvantages is that PSO focuses on the global search while the local search is weaken. However, at the end of the search procedure, the PSO focuses on the local search as all most all the particles converge to small areas which may make the particle swarm trapped in the local minima if no particle find position near the minima at the beginning of search procedure. To improve the optimization performance, the local search is necessary for particle swarm optimization. In this paper, golden ratio is used to determine the size of the search area. Only two positions need to be checked to find whether there are local positions with lower fitness value around a certain particle position. This method is easy to use. It is also tested using several famous benchmarks with high dimensions and big search space to the efficiency of the proposed method.

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collection(s): Conference proceedings
Identifier: http://hdl.handle.net/10210/21329
Identifier: uj:16141
Identifier: uj:16141
Identifier: uj:16141
Identifier: Citation: Sun, Y., Van Wyk, B.J. & Wang, Z. 2012. A new golden ratio local search based particle swarm optimization. 2012 International Conference on Systems and Informatics (ICSAI 2012), Yantai, China 19-20 May, 2012. p. 754-757. ISBN: 978-1-4673-0198-5
Language: English
Rights: ©2012, the authors
Type: Conference proceedings
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Conference proceedings A new golden ratio local search based particle swarm optimization

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