A dynamic particle swarm optimization method applied to global optimizations of engineering inverse problem. Issue 1 (2nd January 2018)

• Record Type: Journal Article
• Authors: Khan, Shafiullah; Yang, Shiyou; Rehman, Obaid Ur
• Is Part Of: Compel. Volume 37:Issue 1(2018)
• Page Start: 98
• Page End: 117
• Publication Date: 2018-01-02
• Subjects: Optimization techniques -- Algorithms -- Particle swarm optimization -- Global optimization -- Inverse problems -- Dynamic inertia weight -- Mutation operator -- Search process; Electrical engineering -- Data Processing -- Periodicals; Electrical engineering -- Mathematics -- Periodicals; Electrical engineering -- Periodicals; Electronics -- Data Processing -- Periodicals; Electronics -- Mathematics -- Periodicals; 621.3
• DOI: 10.1108/COMPEL-08-2016-0352
• Languages: English
• ISSNs: 0332-1649

Abstract

Abstract : Purpose: The aim of this paper is to explore the potential of particle swarm optimization (PSO) algorithm to solve an electromagnetic inverse problem. Design/methodology/approach: A modified PSO algorithm is designed. Findings: The modified PSO algorithm is a more stable, robust and efficient global optimizer for solving the well-known benchmark optimization problems. The new mutation approach preserves the diversity of the population, whereas the proposed dynamic and adaptive parameters maintain a good balance between the exploration and exploitation searches. The numerically experimental results of two case studies demonstrate the merits of the proposed algorithm. Originality/value: Some improvements, such as the design of a new global mutation mechanism and introducing a novel strategy for learning and control parameters, are proposed.