A dynamic particle swarm optimization method applied to global optimizations of engineering inverse problem. Issue 1 (2nd January 2018) - Khan, Shafiullah; Yang, Shiyou; Rehman, Obaid Ur
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.