Particle swarm optimization & gravitational search algorithm in sequential process planning

The purpose of this study is to investigate the application of particle swarm optimization (PSO) and gravitational search algorithm (GSA) in assembly sequence planning problem, to look for the sequence which require the least assembly time. The problem model is an assembly process with 25 parts, whi...

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Main Author:	Lim, Teik Yee
Format:	Thesis
Language:	English
Published:	2013
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/33817/5/LimTiekYeeMFKE2013.pdf
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id	my-utm-ep.33817
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spelling	my-utm-ep.338172017-09-12T08:19:06Z Particle swarm optimization & gravitational search algorithm in sequential process planning 2013-01 Lim, Teik Yee TK Electrical engineering. Electronics Nuclear engineering The purpose of this study is to investigate the application of particle swarm optimization (PSO) and gravitational search algorithm (GSA) in assembly sequence planning problem, to look for the sequence which require the least assembly time. The problem model is an assembly process with 25 parts, which is a high dimension and also NP-hard problem. The study is focused on the comparison between both algorithms and investigation on which method perform better in term of convergence rate and the ability to escape local solution. In this study, the PSO are improved in term of random mechanism and GSA algorithms are improved in term of algorithm in order to improve convergence rate and overcome weak convergence respectively. The quality of randomness is also discussed. The simulation results show that PSO can find better optimum sequence than GSA does. 2013-01 Thesis http://eprints.utm.my/id/eprint/33817/ http://eprints.utm.my/id/eprint/33817/5/LimTiekYeeMFKE2013.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:69726?site_name=Restricted Repository masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Lim, Teik Yee Particle swarm optimization & gravitational search algorithm in sequential process planning
description	The purpose of this study is to investigate the application of particle swarm optimization (PSO) and gravitational search algorithm (GSA) in assembly sequence planning problem, to look for the sequence which require the least assembly time. The problem model is an assembly process with 25 parts, which is a high dimension and also NP-hard problem. The study is focused on the comparison between both algorithms and investigation on which method perform better in term of convergence rate and the ability to escape local solution. In this study, the PSO are improved in term of random mechanism and GSA algorithms are improved in term of algorithm in order to improve convergence rate and overcome weak convergence respectively. The quality of randomness is also discussed. The simulation results show that PSO can find better optimum sequence than GSA does.
format	Thesis
qualification_level	Master's degree
author	Lim, Teik Yee
author_facet	Lim, Teik Yee
author_sort	Lim, Teik Yee
title	Particle swarm optimization & gravitational search algorithm in sequential process planning
title_short	Particle swarm optimization & gravitational search algorithm in sequential process planning
title_full	Particle swarm optimization & gravitational search algorithm in sequential process planning
title_fullStr	Particle swarm optimization & gravitational search algorithm in sequential process planning
title_full_unstemmed	Particle swarm optimization & gravitational search algorithm in sequential process planning
title_sort	particle swarm optimization & gravitational search algorithm in sequential process planning
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2013
url	http://eprints.utm.my/id/eprint/33817/5/LimTiekYeeMFKE2013.pdf
_version_	1747816192405405696

Particle swarm optimization & gravitational search algorithm in sequential process planning

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