An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm

Assembly sequence planning (ASP) becomes one of the major challenges in product design and manufacturing. A good assembly sequence leads to reduced costs and duration in the manufacturing process. However, assembly sequence planning is known to be a classical NP-hard combinatorial optimization probl...

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Main Authors:	Ibrahim, I., Ibrahim, Z., Ahmad, H., Jusof, M.F.M., Yusof, Z.M., Nawawi, S.W., Mubin, M.
Format:	Article
Published:	2015
Subjects:	T Technology (General) TA Engineering (General). Civil engineering (General)
Online Access:	http://link.springer.com/article/10.1007/s00170-015-6857-0 http://link.springer.com/article/10.1007/s00170-015-6857-0 http://eprints.um.edu.my/15700/1/An_assembly_sequence_planning_approach_with_a_rule%2Dbased_multi%2Dstate.pdf

id	um-15700
recordtype	eprints
spelling	um-157002016-03-17T01:29:34Z An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm Ibrahim, I. Ibrahim, Z. Ahmad, H. Jusof, M.F.M. Yusof, Z.M. Nawawi, S.W. Mubin, M. T Technology (General) TA Engineering (General). Civil engineering (General) Assembly sequence planning (ASP) becomes one of the major challenges in product design and manufacturing. A good assembly sequence leads to reduced costs and duration in the manufacturing process. However, assembly sequence planning is known to be a classical NP-hard combinatorial optimization problem; ASP with many product components becomes more difficult to solve. In this paper, an approach based on a new variant of the gravitational search algorithm (GSA) called the rule-based multi-state gravitational search algorithm (RBMSGSA) is used to solve the assembly sequence planning problem. As in the gravitational search algorithm, the RBMSGSA incorporates Newton's law of gravity, the law of motion, and a rule that makes each assembly component of each individual solution occur once based on precedence constraints; the best feasible sequence of assembly can then be determined. To verify the feasibility and performance of the proposed approach, a case study has been performed and a comparison has been conducted against other three approaches based on simulated annealing (SA), a genetic algorithm (GA), and binary particle swarm optimization (BPSO). The experimental results show that the proposed approach has achieved significant improvement in performance over the other methods studied. 2015-07 Article PeerReviewed application/pdf http://eprints.um.edu.my/15700/1/An_assembly_sequence_planning_approach_with_a_rule%2Dbased_multi%2Dstate.pdf http://link.springer.com/article/10.1007/s00170-015-6857-0 Ibrahim, I.; Ibrahim, Z.; Ahmad, H.; Jusof, M.F.M.; Yusof, Z.M.; Nawawi, S.W.; Mubin, M. (2015) An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm. International Journal of Advanced Manufacturing Technology <http://eprints.um.edu.my/view/publication/International_Journal_of_Advanced_Manufacturing_Technology.html>, 79 (5-8). pp. 1363-1376. ISSN 0268-3768 http://eprints.um.edu.my/15700/
repository_type	Digital Repository
institution_category	Local University
institution	University Malaya
building	UM Research Repository
collection	Online Access
topic	T Technology (General) TA Engineering (General). Civil engineering (General)
spellingShingle	T Technology (General) TA Engineering (General). Civil engineering (General) Ibrahim, I. Ibrahim, Z. Ahmad, H. Jusof, M.F.M. Yusof, Z.M. Nawawi, S.W. Mubin, M. An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm
description	Assembly sequence planning (ASP) becomes one of the major challenges in product design and manufacturing. A good assembly sequence leads to reduced costs and duration in the manufacturing process. However, assembly sequence planning is known to be a classical NP-hard combinatorial optimization problem; ASP with many product components becomes more difficult to solve. In this paper, an approach based on a new variant of the gravitational search algorithm (GSA) called the rule-based multi-state gravitational search algorithm (RBMSGSA) is used to solve the assembly sequence planning problem. As in the gravitational search algorithm, the RBMSGSA incorporates Newton's law of gravity, the law of motion, and a rule that makes each assembly component of each individual solution occur once based on precedence constraints; the best feasible sequence of assembly can then be determined. To verify the feasibility and performance of the proposed approach, a case study has been performed and a comparison has been conducted against other three approaches based on simulated annealing (SA), a genetic algorithm (GA), and binary particle swarm optimization (BPSO). The experimental results show that the proposed approach has achieved significant improvement in performance over the other methods studied.
format	Article
author	Ibrahim, I. Ibrahim, Z. Ahmad, H. Jusof, M.F.M. Yusof, Z.M. Nawawi, S.W. Mubin, M.
author_facet	Ibrahim, I. Ibrahim, Z. Ahmad, H. Jusof, M.F.M. Yusof, Z.M. Nawawi, S.W. Mubin, M.
author_sort	Ibrahim, I.
title	An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm
title_short	An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm
title_full	An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm
title_fullStr	An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm
title_full_unstemmed	An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm
title_sort	assembly sequence planning approach with a rule-based multi-state gravitational search algorithm
publishDate	2015
url	http://link.springer.com/article/10.1007/s00170-015-6857-0 http://link.springer.com/article/10.1007/s00170-015-6857-0 http://eprints.um.edu.my/15700/1/An_assembly_sequence_planning_approach_with_a_rule%2Dbased_multi%2Dstate.pdf
first_indexed	2018-09-06T06:32:11Z
last_indexed	2018-09-06T06:32:11Z
_version_	1610838736849862656

An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm

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