relation: https://khub.utp.edu.my/scholars/2922/
title: A hybrid PSO approach for solving non-convex optimization problems
creator: Ganesan, T.
creator: Vasant, P.
creator: Elamvazuthy, I.
description: The aim of this paper is to propose an improved particle swarm optimization (PSO) procedure for non-convex optimization problems. This approach embeds classical methods which are the Kuhn-Tucker (KT) conditions and the Hessian matrix into the fitness function. This generates a semi-classical PSO algorithm (SPSO). The classical component improves the PSO method in terms of its capacity to search for optimal solutions in non-convex scenarios. In this work, the development and the testing of the refined the SPSO algorithm was carried out. The SPSO algorithm was tested against two engineering design problems which were; 'optimization of the design of a pressure vessel' (P1) and the 'optimization of the design of a tension/compression spring' (P2). The computational performance of the SPSO algorithm was then compared against the modified particle swarm optimization (PSO) algorithm of previous work on the same engineering problems. Comparative studies and analysis were then carried out based on the optimized results. It was observed that the SPSO provides a better minimum with a higher quality constraint satisfaction as compared to the PSO approach in the previous work. Copyright © Silesian University of Technology, 2012.
date: 2012
type: Article
type: PeerReviewed
identifier:   Ganesan, T. and Vasant, P. and Elamvazuthy, I.  (2012) A hybrid PSO approach for solving non-convex optimization problems.  Archives of Control Sciences, 22 (1).  pp. 87-105.  ISSN 12302384     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84864554125&doi=10.2478%2fv10170-011-0014-2&partnerID=40&md5=165cdf7cb7bcb2dd5b74eb75a578ae21
relation: 10.2478/v10170-011-0014-2
identifier: 10.2478/v10170-011-0014-2