An improved particle swarm optimization algorithm combined with piecewise linear chaotic map
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
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Detail(s)
Original language | English |
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Pages (from-to) | 1637-1645 |
Journal / Publication | Applied Mathematics and Computation |
Volume | 190 |
Issue number | 2 |
Publication status | Published - 15 Jul 2007 |
Link(s)
Abstract
Particle swarm optimization (PSO) has gained increasing attention in tackling complex optimization problems. Its further superiority when hybridized with other search techniques is also shown. Chaos, with the properties of ergodicity and stochasticity, is definitely a good candidate, but currently only the well-known logistic map is prevalently used. In this paper, the performance and deficiencies of schemes coupling chaotic search into PSO are analyzed. Then, the piecewise linear chaotic map (PWLCM) is introduced to perform the chaotic search. An improved PSO algorithm combined with PWLCM (PWLCPSO) is proposed subsequently, and experimental results verify its great superiority. © 2007 Elsevier Inc. All rights reserved.
Research Area(s)
- Chaotic optimization, Particle swarm optimization, Piecewise linear chaotic map
Citation Format(s)
An improved particle swarm optimization algorithm combined with piecewise linear chaotic map. / Xiang, Tao; Liao, Xiaofeng; Wong, Kwok-wo.
In: Applied Mathematics and Computation, Vol. 190, No. 2, 15.07.2007, p. 1637-1645.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review