Dynamic parameterizations of particle swarm optimization and genetic algorithm for facility layout problem

Surrounded by an assortment of intelligent and efficient search entities, the hybridization of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are proven to be a comprehensive tool for solving different kinds of optimization problems due to their contradictive working approaches. In add...

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Main Authors: Masrom, S., Abidin, S.Z.Z., Omar, N., Rahman, A.S.A., Rizman, Z.I.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.19511 /
Published: Asian Research Publishing Network 2017
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020092904&partnerID=40&md5=8ca26eb4239b59b51b6a60468038e607
http://eprints.utp.edu.my/19511/
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spelling utp-eprints.195112018-04-20T06:05:19Z Dynamic parameterizations of particle swarm optimization and genetic algorithm for facility layout problem Masrom, S. Abidin, S.Z.Z. Omar, N. Rahman, A.S.A. Rizman, Z.I. Surrounded by an assortment of intelligent and efficient search entities, the hybridization of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are proven to be a comprehensive tool for solving different kinds of optimization problems due to their contradictive working approaches. In addition, the two algorithms have achieved a remarkable improvement from the adaption of dynamic parameterizations. In this work, dynamic parameterized mutation and crossover are individually and in combination hybridized with a PSO implementation. The performances of different dynamic parameterizations of the hybrid algorithms in solving facility layout problem are compared with single PSO. The comparison revealed that the proposed technique is more effective. Asian Research Publishing Network 2017 Article PeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020092904&partnerID=40&md5=8ca26eb4239b59b51b6a60468038e607 Masrom, S. and Abidin, S.Z.Z. and Omar, N. and Rahman, A.S.A. and Rizman, Z.I. (2017) Dynamic parameterizations of particle swarm optimization and genetic algorithm for facility layout problem. ARPN Journal of Engineering and Applied Sciences, 12 (10). pp. 3195-3201. http://eprints.utp.edu.my/19511/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Surrounded by an assortment of intelligent and efficient search entities, the hybridization of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are proven to be a comprehensive tool for solving different kinds of optimization problems due to their contradictive working approaches. In addition, the two algorithms have achieved a remarkable improvement from the adaption of dynamic parameterizations. In this work, dynamic parameterized mutation and crossover are individually and in combination hybridized with a PSO implementation. The performances of different dynamic parameterizations of the hybrid algorithms in solving facility layout problem are compared with single PSO. The comparison revealed that the proposed technique is more effective.
format Article
author Masrom, S.
Abidin, S.Z.Z.
Omar, N.
Rahman, A.S.A.
Rizman, Z.I.
spellingShingle Masrom, S.
Abidin, S.Z.Z.
Omar, N.
Rahman, A.S.A.
Rizman, Z.I.
Dynamic parameterizations of particle swarm optimization and genetic algorithm for facility layout problem
author_sort Masrom, S.
title Dynamic parameterizations of particle swarm optimization and genetic algorithm for facility layout problem
title_short Dynamic parameterizations of particle swarm optimization and genetic algorithm for facility layout problem
title_full Dynamic parameterizations of particle swarm optimization and genetic algorithm for facility layout problem
title_fullStr Dynamic parameterizations of particle swarm optimization and genetic algorithm for facility layout problem
title_full_unstemmed Dynamic parameterizations of particle swarm optimization and genetic algorithm for facility layout problem
title_sort dynamic parameterizations of particle swarm optimization and genetic algorithm for facility layout problem
publisher Asian Research Publishing Network
publishDate 2017
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020092904&partnerID=40&md5=8ca26eb4239b59b51b6a60468038e607
http://eprints.utp.edu.my/19511/
_version_ 1741196218355154944
score 11.62408

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