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...
| Main Authors: | , , , , , , |
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| Format: | Article |
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Springer
2015
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| _version_ | 1796860370011291648 |
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| author | A. Ibrahim, Ismail Ibrahim, Zuwairie Ahmad, Hamzah Mat Jusof, Mohd. Falfazli Md. Yusof, Zulkifli Nawawi, Sophan Wahyudi Mubin, Marizan |
| author_facet | A. Ibrahim, Ismail Ibrahim, Zuwairie Ahmad, Hamzah Mat Jusof, Mohd. Falfazli Md. Yusof, Zulkifli Nawawi, Sophan Wahyudi Mubin, Marizan |
| author_sort | A. Ibrahim, Ismail |
| collection | ePrints |
| 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 |
| first_indexed | 2024-03-05T19:40:21Z |
| format | Article |
| id | utm.eprints-57742 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T19:40:21Z |
| publishDate | 2015 |
| publisher | Springer |
| record_format | dspace |
| spelling | utm.eprints-577422017-02-01T01:03:45Z http://eprints.utm.my/57742/ An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm A. Ibrahim, Ismail Ibrahim, Zuwairie Ahmad, Hamzah Mat Jusof, Mohd. Falfazli Md. Yusof, Zulkifli Nawawi, Sophan Wahyudi Mubin, Marizan TK Electrical engineering. Electronics Nuclear engineering 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 Springer 2015-03 Article PeerReviewed A. Ibrahim, Ismail and Ibrahim, Zuwairie and Ahmad, Hamzah and Mat Jusof, Mohd. Falfazli and Md. Yusof, Zulkifli and Nawawi, Sophan Wahyudi and Mubin, Marizan (2015) An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm. International Journal of Advanced Manufacturing Technology, 79 . pp. 1363-1376. ISSN 0268-3768 http://dx.doi.org/10.1007/s00170-015-6857-0 DOI:10.1007/s00170-015-6857-0 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering A. Ibrahim, Ismail Ibrahim, Zuwairie Ahmad, Hamzah Mat Jusof, Mohd. Falfazli Md. Yusof, Zulkifli Nawawi, Sophan Wahyudi Mubin, Marizan An assembly sequence planning approach with a rule-based multi-state gravitational search algorithm |
| title | 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_short | 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 |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
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