relation: https://khub.utp.edu.my/scholars/2079/
title: Simple heuristics-based selection of guides for multi-objective PSO with an application to electrical distribution system planning
creator: Sahoo, N.C.
creator: Ganguly, S.
creator: Das, D.
description: In multi-objective particle swarm optimization (MOPSO), a proper selection of local guides significantly influences detection of non-dominated solutions in the objective/solution space and, hence, the convergence characteristics towards the Pareto-optimal set. This paper presents an algorithm based on simple heuristics for selection of local guides in MOPSO, named as HSG-MOPSO (Heuristics-based-Selection-of-Guides in MOPSO). In the HSG-MOPSO, the set of potential guides (in a PSO iteration) consists of the non-dominated solutions (which are normally stored in an elite archive) and some specifically chosen dominated solutions. Thus, there are two types of local guides in the HSG-MOPSO, i.e., non-dominated and dominated guides; they are named so as to signify whether the chosen guide is a non-dominated or a dominated solution. In any iteration, a guide, from the set of available guides, is suitably selected for each population member. Some specified proportion of the current population members follow their respective nearest non-dominated guides and the rest follow their respective nearest dominated guides. The proposed HSG-MOPSO is firstly evaluated on a number of multi-objective benchmark problems along with investigations on the controlling parameters of the guide selection algorithm. The performance of the proposed method is compared with those of two well-known guide selection methods for evolutionary multi-objective optimization, namely the Sigma method and the Strength Pareto Evolutionary Algorithm-2 (SPEA2) implemented in PSO framework. Finally, the HSG-MOPSO is evaluated on a more involved real world problem, i.e., multi-objective planning of electrical distribution system. Simulation results are reported and analyzed to illustrate the viability of the proposed guide selection method for MOPSO. © 2011 Elsevier Ltd. All rights reserved.
date: 2011
type: Article
type: PeerReviewed
identifier:   Sahoo, N.C. and Ganguly, S. and Das, D.  (2011) Simple heuristics-based selection of guides for multi-objective PSO with an application to electrical distribution system planning.  Engineering Applications of Artificial Intelligence, 24 (4).  pp. 567-585.  ISSN 09521976     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-79953655383&doi=10.1016%2fj.engappai.2011.02.007&partnerID=40&md5=a5cf7c9146872eb591548c961a63c479
relation: 10.1016/j.engappai.2011.02.007
identifier: 10.1016/j.engappai.2011.02.007