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Chaos embedded particle swarm optimization algorithms

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  • Alatas, Bilal
  • Akin, Erhan
  • Ozer, A. Bedri

Abstract

This paper proposes new particle swarm optimization (PSO) methods that use chaotic maps for parameter adaptation. This has been done by using of chaotic number generators each time a random number is needed by the classical PSO algorithm. Twelve chaos-embedded PSO methods have been proposed and eight chaotic maps have been analyzed in the benchmark functions. It has been detected that coupling emergent results in different areas, like those of PSO and complex dynamics, can improve the quality of results in some optimization problems. It has been also shown that, some of the proposed methods have somewhat increased the solution quality, that is in some cases they improved the global searching capability by escaping the local solutions.

Suggested Citation

  • Alatas, Bilal & Akin, Erhan & Ozer, A. Bedri, 2009. "Chaos embedded particle swarm optimization algorithms," Chaos, Solitons & Fractals, Elsevier, vol. 40(4), pages 1715-1734.
    • Handle: RePEc:eee:chsofr:v:40:y:2009:i:4:p:1715-1734
    DOI: 10.1016/j.chaos.2007.09.063
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    Cited by:

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    14. Tatsumi, Keiji & Obita, Yoshinori & Tanino, Tetsuzo, 2009. "Chaos generator exploiting a gradient model with sinusoidal perturbations for global optimization," Chaos, Solitons & Fractals, Elsevier, vol. 42(3), pages 1705-1723.
    15. Acharjee, P. & Mallick, S. & Thakur, S.S. & Ghoshal, S.P., 2011. "Detection of maximum loadability limits and weak buses using Chaotic PSO considering security constraints," Chaos, Solitons & Fractals, Elsevier, vol. 44(8), pages 600-612.
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