Optimisation of Assembly Line Balancing Type-E with Resource Constraints using NSGA-II

Assembly line balancing of Type-E problem (ALB-E) is an attempt to assign the tasks to the various workstations along the line so that the precedence relations are satisfied and some performance measures are optimised. A majority of the recent studies in ALB-E assume that any assembly task can be a...

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Main Authors: Masitah, Jusop, M. F. F., Ab Rashid
Format: Article
Language:English
Published: Trans Tech Publications, Switzerland 2016
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/13050/1/fkm-2016-masitah-Optimisation%20of%20Assembly%20Line%20Balancing.pdf
http://umpir.ump.edu.my/id/eprint/13050/
http://dx.doi.org/10.4028/www.scientific.net/KEM.701.195
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Institution: Universiti Malaysia Pahang
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spelling my.ump.umpir.130502016-08-04T06:19:53Z http://umpir.ump.edu.my/id/eprint/13050/ Optimisation of Assembly Line Balancing Type-E with Resource Constraints using NSGA-II Masitah, Jusop M. F. F., Ab Rashid TS Manufactures Assembly line balancing of Type-E problem (ALB-E) is an attempt to assign the tasks to the various workstations along the line so that the precedence relations are satisfied and some performance measures are optimised. A majority of the recent studies in ALB-E assume that any assembly task can be assigned to any workstation. This assumption lead to higher usage of resource required in assembly line. This research studies assembly line balancing of Type-E problem with resource constraint (ALBE-RC) for a single-model. In this work, three objective functions are considered, i.e. minimise number of workstation, cycle time and number of resources. In this paper, an Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) has been proposed to optimise the problem. Six benchmark problems have been used to test the optimisation algorithm and the results are compared to multi-objective genetic algorithm (MOGA) and hybrid genetic algorithm (HGA). From the computational test, it was found NSGA-II has the ability to explore search space, has better accuracy of solution and also has a uniformly spaced solution. In future, a research to improve the solution accuracy is proposed to enhance the performance of the algorithm. Trans Tech Publications, Switzerland 2016-07-11 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/13050/1/fkm-2016-masitah-Optimisation%20of%20Assembly%20Line%20Balancing.pdf Masitah, Jusop and M. F. F., Ab Rashid (2016) Optimisation of Assembly Line Balancing Type-E with Resource Constraints using NSGA-II. Key Engineering Materials, 701. pp. 195-199. ISSN 1662-9795 http://dx.doi.org/10.4028/www.scientific.net/KEM.701.195 DOI: 10.4028/www.scientific.net/KEM.701.195
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TS Manufactures
spellingShingle TS Manufactures
Masitah, Jusop
M. F. F., Ab Rashid
Optimisation of Assembly Line Balancing Type-E with Resource Constraints using NSGA-II
description Assembly line balancing of Type-E problem (ALB-E) is an attempt to assign the tasks to the various workstations along the line so that the precedence relations are satisfied and some performance measures are optimised. A majority of the recent studies in ALB-E assume that any assembly task can be assigned to any workstation. This assumption lead to higher usage of resource required in assembly line. This research studies assembly line balancing of Type-E problem with resource constraint (ALBE-RC) for a single-model. In this work, three objective functions are considered, i.e. minimise number of workstation, cycle time and number of resources. In this paper, an Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) has been proposed to optimise the problem. Six benchmark problems have been used to test the optimisation algorithm and the results are compared to multi-objective genetic algorithm (MOGA) and hybrid genetic algorithm (HGA). From the computational test, it was found NSGA-II has the ability to explore search space, has better accuracy of solution and also has a uniformly spaced solution. In future, a research to improve the solution accuracy is proposed to enhance the performance of the algorithm.
format Article
author Masitah, Jusop
M. F. F., Ab Rashid
author_facet Masitah, Jusop
M. F. F., Ab Rashid
author_sort Masitah, Jusop
title Optimisation of Assembly Line Balancing Type-E with Resource Constraints using NSGA-II
title_short Optimisation of Assembly Line Balancing Type-E with Resource Constraints using NSGA-II
title_full Optimisation of Assembly Line Balancing Type-E with Resource Constraints using NSGA-II
title_fullStr Optimisation of Assembly Line Balancing Type-E with Resource Constraints using NSGA-II
title_full_unstemmed Optimisation of Assembly Line Balancing Type-E with Resource Constraints using NSGA-II
title_sort optimisation of assembly line balancing type-e with resource constraints using nsga-ii
publisher Trans Tech Publications, Switzerland
publishDate 2016
url http://umpir.ump.edu.my/id/eprint/13050/1/fkm-2016-masitah-Optimisation%20of%20Assembly%20Line%20Balancing.pdf
http://umpir.ump.edu.my/id/eprint/13050/
http://dx.doi.org/10.4028/www.scientific.net/KEM.701.195
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