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An improved particle swarm optimization algorithm combined with piecewise linear chaotic map. (English) Zbl 1122.65363
Summary: 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 is proposed subsequently, and experimental results verify its great superiority.
MSC:
65K05Mathematical programming (numerical methods)
90C15Stochastic programming