A dynamic particle swarm optimization method applied to global optimizations of engineering inverse problem

Abstract

PurposeThe aim of this paper is to explore the potential of particle swarm optimization (PSO) algorithm to solve an electromagnetic inverse problem.Design/methodology/approachA modified PSO algorithm is designed.FindingsThe 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/valueSome improvements, such as the design of a new global mutation mechanism and introducing a novel strategy for learning and control parameters, are proposed.