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

Shafiullah Khan (College of Electrical Engineering, Zhejiang University, Hangzhou, China)
Shiyou Yang (College of Electrical Engineering, Zhejiang University, Hangzhou, China)
Obaid Ur Rehman (College of Electrical Engineering, Zhejiang University, Hangzhou, China)
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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.

Keywords

Citation

Khan, S., Yang, S. and Rehman, O.U. (2018), "A dynamic particle swarm optimization method applied to global optimizations of engineering inverse problem", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 37 No. 1, pp. 98-117. https://doi.org/10.1108/COMPEL-08-2016-0352

Publisher

:

Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

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