A modified PSO algorithm with dynamic parameters for solving complex engineering design problem. Issue 11 (2nd November 2018)

• Record Type: Journal Article
• Authors: Khan, Shafiullah; Kamran, M.; Rehman, Obaid Ur; Liu, Lei; Yang, Shiyou
• Is Part Of: International journal of computer mathematics. Volume 95:Issue 11(2018)
• Page Start: 2308
• Page End: 2329
• Publication Date: 2018-11-02
• Subjects: Dynamic learning parameters -- dynamic inertia weight -- particle swarm optimization -- global optimization -- inverse problem; 20B40 -- 90C26 -- 97R40 -- 15A29 -- 78A25; Computers -- Periodicals; Numerical analysis -- Periodicals; Automation -- Periodicals; 004.0151
• DOI: 10.1080/00207160.2017.1387252
• Languages: English
• ISSNs: 0020-7160

Abstract

ABSTRACT: This paper proposed a new approach of particle swarm optimization (PSO). The proposed modified PSO algorithm is equipped with some specially designed mechanisms of adaptively updating algorithm parameters to preserve the diversity of the swarm and to keep the balance between exploration and exploitation searches. All these mechanisms help the algorithm to avoid the premature convergence and to strengthen its robustness. Experiments are conducted on different complicated, unimodal and multimodal test functions, as well as a typical engineering inverse problem, the TEAM Workshop problem 22. The numerical results illustrate that the proposed PSO shows better performance as compared to other well developed evolutionary algorithms.