A Perturbation-Based Chaotic Particle Swarm Optimization Searching around Multiple Personal Best Solutions. Issue 4 (1st July 2018)

• Record Type: Journal Article
• Authors: Kuwabara, Tomoki; Mineoka, Haruhiko; Tatsumi, Keiji
• Is Part Of: SICE journal of control, measurement, and system integration. Volume 11:Issue 4(2018)
• Page Start: 349
• Page End: 356
• Publication Date: 2018-07-01
• Subjects: chaotic system -- particle swarm optimization -- global optimization -- metaheuristics
• DOI: 10.9746/jcmsi.11.349
• Languages: English
• ISSNs: 1882-4889

Abstract

Abstract : In this paper, we deal with the particle swarm optimization (PSO) which is one of metaheuristic methods for global optimization. In this paper, we propose a PSO method using a chaotic system, where each particle keeps its best solution called the pbest, and it searches around multiple pbests of which function values are not more than that of one's own pbest. Since the proposed method updates the particle's position by using a perturbation-based chaotic system, each particle is not trapped at any local minimum solution. In addition, the method can be expected to search for solutions effectively by keeping a balance between the expansion of the searching area and the limitation of the area based on the qualities of the multiple pbests. Through numerical experiments, we verify the advantages of the proposed method.