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Particle swarm optimization with stochastic selection of perturbation-based chaotic updating system

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  • Tatsumi, Keiji
  • Ibuki, Takeru
  • Tanino, Tetsuzo

Abstract

In this paper, we consider the particle swarm optimization (PSO). In particular, we focus on an improved PSO called the CPSO-VQO, which uses a perturbation-based chaotic system and a threshold-based method of selecting from the standard and chaotic updating systems for each particle on the basis of the difference vector between its pbest and the gbest. Although it was reported that the CPSO-VQO performs well, it is not easy to select an amplitude of the perturbation and a threshold appropriately for an effective search. This is because the bifurcation structure of the chaotic system depends on the difference vector, and the difference vector varies widely between different stages of the search and between different problems.

Suggested Citation

  • Tatsumi, Keiji & Ibuki, Takeru & Tanino, Tetsuzo, 2015. "Particle swarm optimization with stochastic selection of perturbation-based chaotic updating system," Applied Mathematics and Computation, Elsevier, vol. 269(C), pages 904-929.
    • Handle: RePEc:eee:apmaco:v:269:y:2015:i:c:p:904-929
    DOI: 10.1016/j.amc.2015.07.098
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    References listed on IDEAS

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    1. Alatas, Bilal & Akin, Erhan & Ozer, A. Bedri, 2009. "Chaos embedded particle swarm optimization algorithms," Chaos, Solitons & Fractals, Elsevier, vol. 40(4), pages 1715-1734.
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    3. Liu, Bo & Wang, Ling & Jin, Yi-Hui & Tang, Fang & Huang, De-Xian, 2005. "Improved particle swarm optimization combined with chaos," Chaos, Solitons & Fractals, Elsevier, vol. 25(5), pages 1261-1271.
    4. Chuanwen, Jiang & Bompard, Etorre, 2005. "A hybrid method of chaotic particle swarm optimization and linear interior for reactive power optimisation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 68(1), pages 57-65.
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