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Particle swarm optimization combined with normative knowledge applied to Loney's solenoid design

Particle swarm optimization combined with normative knowledge applied to Loney's solenoid design Purpose – The purpose of this paper is to show, on a widely used benchmark problem, that normative knowledge concepts can be incorporated into particle swarm optimization (PSO) algorithms in order to improve their search ability. Design/methodology/approach – Normative knowledge concepts are used within the framework of PSO algorithms in order to influence the cognitive and social components of the particle behaviour. Findings – It is shown that the proposed algorithm can significantly improve the performance of PSO on the selected benchmark problem, in terms of both best and average solutions. Research limitations/implications – Although the chosen benchmark is considered to be representative of typical electromagnetic problems, different test cases may give less satisfactory results. Practical implications – The proposed approach appears to be an efficient general purpose stochastic optimizer for electromagnetic design problems. Originality/value – This paper introduces the use of normative knowledge concepts to control the cognitive and social components of PSO algorithms. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering Emerald Publishing

Particle swarm optimization combined with normative knowledge applied to Loney's solenoid design

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References (12)

Publisher
Emerald Publishing
Copyright
Copyright © 2009 Emerald Group Publishing Limited. All rights reserved.
ISSN
0332-1649
DOI
10.1108/03321640910969412
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to show, on a widely used benchmark problem, that normative knowledge concepts can be incorporated into particle swarm optimization (PSO) algorithms in order to improve their search ability. Design/methodology/approach – Normative knowledge concepts are used within the framework of PSO algorithms in order to influence the cognitive and social components of the particle behaviour. Findings – It is shown that the proposed algorithm can significantly improve the performance of PSO on the selected benchmark problem, in terms of both best and average solutions. Research limitations/implications – Although the chosen benchmark is considered to be representative of typical electromagnetic problems, different test cases may give less satisfactory results. Practical implications – The proposed approach appears to be an efficient general purpose stochastic optimizer for electromagnetic design problems. Originality/value – This paper introduces the use of normative knowledge concepts to control the cognitive and social components of PSO algorithms.

Journal

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic EngineeringEmerald Publishing

Published: Sep 11, 2009

Keywords: Electromagnetism; Optimization techniques; Algorithmic languages

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