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

Keiji Tatsumi, Takeru Ibuki and Tetsuzo Tanino

Applied Mathematics and Computation, 2015, vol. 269, issue C, 904-929

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.

Keywords: Chaotic system; Particle swarm optimization; Metaheuristics; Snap-back repeller; Global optimization (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:269:y:2015:i:c:p:904-929

DOI: 10.1016/j.amc.2015.07.098

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