Title: Mean particle swarm optimisation for function optimisation

Authors: Kusum Deep, Jagdish Chand Bansal

Addresses: Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee – 247667, India. ' Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee – 247667, India

Abstract: In this paper, a new particle swarm optimisation algorithm, called MeanPSO, is presented, based on a novel philosophy by modifying the velocity update equation. This is done by replacing two terms of original velocity update equation by two new terms based on the linear combination of pbest and gbest. Its performance is compared with the standard PSO (SPSO) by testing it on a set of 15 scalable and 15 nonscalable test problems. Based on the numerical and graphical analyses of results it is shown that the MeanPSO outperforms the SPSO, in terms of efficiency, reliability, accuracy and stability.

Keywords: particle swarm optimisation; PSO; MeanPSO; global optimisation; velocity update equation.

DOI: 10.1504/IJCISTUDIES.2009.025339

International Journal of Computational Intelligence Studies, 2009 Vol.1 No.1, pp.72 - 92

Published online: 19 May 2009 *

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