Bio-inspired and musical-harmony approaches for machine allocation optimization in flexible manufacturing system

Manufacturing industries need to constantly adjust to the rapid pace of change in the market. Many of the manufactured products often have a very short life cycle. These scenarios imply the need to improve the efficiency of capacity planning, an important aspect of machine allocation plan that is kn...

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Main Author:	Yusof, Umi Kalsom
Format:	Thesis
Language:	English
Published:	2013
Subjects:	TS Manufactures
Online Access:	http://eprints.utm.my/id/eprint/33767/5/UmiKalsomYusofPFSKSM2013.pdf
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id	my-utm-ep.33767
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spelling	my-utm-ep.337672017-07-24T01:38:50Z Bio-inspired and musical-harmony approaches for machine allocation optimization in flexible manufacturing system 2013-02 Yusof, Umi Kalsom TS Manufactures Manufacturing industries need to constantly adjust to the rapid pace of change in the market. Many of the manufactured products often have a very short life cycle. These scenarios imply the need to improve the efficiency of capacity planning, an important aspect of machine allocation plan that is known for its complexity. Two common approaches to solve the machine allocation problem include optimization-based methods and heuristic oriented methods. Although optimization-based methods are robust in their applicability, they tend to become impractical when the problem size increases, while heuristic approaches are mainly dependent on rules and constraints of an individual problem. Due to this, heuristic approaches always face difficulties to estimate results in a changed environment. The use of new and innovative meta-heuristic searching techniques of populationbased algorithms in this research can overcome these limitations. The objectives of this research are to minimize the system unbalance and machine makespan utilization, and to increase throughput taking into consideration of the technological constraints. Population-based algorithms that consist of constraint-chromosome genetic algorithm (CCGA), constraint-vector harmony search (CVHS) and hybrid of constraint-chromosome genetic algorithm and harmony search (H-CCGaHs) were adopted. To ensure the feasibility of the results and to promote for a faster convergence, the right mapping chromosome or harmony memory representation was applied to the domain problem in all the three algorithms. Genetic algorithm is known for its exploitative ability, whereas harmony search is recognized for its explorative capability. H-CCGaHs combines these strengths to produce a more effective algorithm where both aspects will be optimized and helps avoid getting trapped in local minima. These three algorithms (CCGA, CVHS and H-CCGaHs) were tested on both benchmark data (10 datasets) and industrial data (5 datasets). The results indicated that the proposed H-CCGaHs achieves better results, with faster convergence and a reasonable time to run the algorithm. 2013-02 Thesis http://eprints.utm.my/id/eprint/33767/ http://eprints.utm.my/id/eprint/33767/5/UmiKalsomYusofPFSKSM2013.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:69301?site_name=Restricted Repository phd doctoral Universiti Teknologi Malaysia, Faculty of Computing Faculty of Computing
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TS Manufactures
spellingShingle	TS Manufactures Yusof, Umi Kalsom Bio-inspired and musical-harmony approaches for machine allocation optimization in flexible manufacturing system
description	Manufacturing industries need to constantly adjust to the rapid pace of change in the market. Many of the manufactured products often have a very short life cycle. These scenarios imply the need to improve the efficiency of capacity planning, an important aspect of machine allocation plan that is known for its complexity. Two common approaches to solve the machine allocation problem include optimization-based methods and heuristic oriented methods. Although optimization-based methods are robust in their applicability, they tend to become impractical when the problem size increases, while heuristic approaches are mainly dependent on rules and constraints of an individual problem. Due to this, heuristic approaches always face difficulties to estimate results in a changed environment. The use of new and innovative meta-heuristic searching techniques of populationbased algorithms in this research can overcome these limitations. The objectives of this research are to minimize the system unbalance and machine makespan utilization, and to increase throughput taking into consideration of the technological constraints. Population-based algorithms that consist of constraint-chromosome genetic algorithm (CCGA), constraint-vector harmony search (CVHS) and hybrid of constraint-chromosome genetic algorithm and harmony search (H-CCGaHs) were adopted. To ensure the feasibility of the results and to promote for a faster convergence, the right mapping chromosome or harmony memory representation was applied to the domain problem in all the three algorithms. Genetic algorithm is known for its exploitative ability, whereas harmony search is recognized for its explorative capability. H-CCGaHs combines these strengths to produce a more effective algorithm where both aspects will be optimized and helps avoid getting trapped in local minima. These three algorithms (CCGA, CVHS and H-CCGaHs) were tested on both benchmark data (10 datasets) and industrial data (5 datasets). The results indicated that the proposed H-CCGaHs achieves better results, with faster convergence and a reasonable time to run the algorithm.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Yusof, Umi Kalsom
author_facet	Yusof, Umi Kalsom
author_sort	Yusof, Umi Kalsom
title	Bio-inspired and musical-harmony approaches for machine allocation optimization in flexible manufacturing system
title_short	Bio-inspired and musical-harmony approaches for machine allocation optimization in flexible manufacturing system
title_full	Bio-inspired and musical-harmony approaches for machine allocation optimization in flexible manufacturing system
title_fullStr	Bio-inspired and musical-harmony approaches for machine allocation optimization in flexible manufacturing system
title_full_unstemmed	Bio-inspired and musical-harmony approaches for machine allocation optimization in flexible manufacturing system
title_sort	bio-inspired and musical-harmony approaches for machine allocation optimization in flexible manufacturing system
granting_institution	Universiti Teknologi Malaysia, Faculty of Computing
granting_department	Faculty of Computing
publishDate	2013
url	http://eprints.utm.my/id/eprint/33767/5/UmiKalsomYusofPFSKSM2013.pdf
_version_	1747816180129726464

Bio-inspired and musical-harmony approaches for machine allocation optimization in flexible manufacturing system

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