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

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.

Citation

dos Santos Coelho, L. and Alotto, P. (2009), "Particle swarm optimization combined with normative knowledge applied to Loney's solenoid design", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 28 No. 5, pp. 1155-1161. https://doi.org/10.1108/03321640910969412