Benders decomposition algorithm for MMAL balancing problem with express parallel line
Mixed-model assembly line (MMAL) could be a form of line capable of manufacturing numerous models of a product on one line. In this paper, a particular parallel MMAL balancing problem is studied in a make-to-order (MTO) production system. Customer’s satisfaction is examined in this paper by consider...
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| Veröffentlicht in: | Operational research Jg. 25; H. 3; S. 74 |
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01.09.2025
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| Abstract | Mixed-model assembly line (MMAL) could be a form of line capable of manufacturing numerous models of a product on one line. In this paper, a particular parallel MMAL balancing problem is studied in a make-to-order (MTO) production system. Customer’s satisfaction is examined in this paper by considering two parallel assembly lines: a main assembly line for normal orders and an express parallel line capable of quick assembling of models for priority orders. Furthermore, due to change of customer demands in MTO environment, the rebalancing problem is considered to maximize flexibility in the lead-time. To solve this multi-objective balancing problem, an integrated Benders Decomposition Algorithm (BDA) based on the LP-metric method is introduced. In large-size problems, the presented model is compared with the non-dominated sorting genetic algorithm (NSGA-II) and Multi-objective Particle Swarm Optimization (MOPSO) and the effectiveness of the proposed integrated BDA is investigated based on computational experiments. The percentage of gap from optimal solutions in the integrated BDA is zero and this gap changes from 0 to 4.2 in the NSGA-II algorithm and from 1 to 4.4 in the MOPSO algorithm. With regard to run times, the results obtained from NSGA-II are relatively superior in calculation time compared to the integrated BDA. However, the solution times for the integrated BDA are not large with respect to exact solutions of this algorithm and dimensions of problems. |
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| AbstractList | Mixed-model assembly line (MMAL) could be a form of line capable of manufacturing numerous models of a product on one line. In this paper, a particular parallel MMAL balancing problem is studied in a make-to-order (MTO) production system. Customer’s satisfaction is examined in this paper by considering two parallel assembly lines: a main assembly line for normal orders and an express parallel line capable of quick assembling of models for priority orders. Furthermore, due to change of customer demands in MTO environment, the rebalancing problem is considered to maximize flexibility in the lead-time. To solve this multi-objective balancing problem, an integrated Benders Decomposition Algorithm (BDA) based on the LP-metric method is introduced. In large-size problems, the presented model is compared with the non-dominated sorting genetic algorithm (NSGA-II) and Multi-objective Particle Swarm Optimization (MOPSO) and the effectiveness of the proposed integrated BDA is investigated based on computational experiments. The percentage of gap from optimal solutions in the integrated BDA is zero and this gap changes from 0 to 4.2 in the NSGA-II algorithm and from 1 to 4.4 in the MOPSO algorithm. With regard to run times, the results obtained from NSGA-II are relatively superior in calculation time compared to the integrated BDA. However, the solution times for the integrated BDA are not large with respect to exact solutions of this algorithm and dimensions of problems. |
| ArticleNumber | 74 |
| Author | Tanhaie, F. |
| Author_xml | – sequence: 1 givenname: F. orcidid: 0000-0002-1388-9289 surname: Tanhaie fullname: Tanhaie, F. email: fahimeh.tanhaie@kub.ac.ir organization: Industrial Engineering Department, Faculty of Basic Science and Engineering, Kosar University of Bojnord |
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| Keywords | Benders decomposition algorithm Mixed-model assembly line Make-to-order Priority orders Parallel lines |
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| Snippet | Mixed-model assembly line (MMAL) could be a form of line capable of manufacturing numerous models of a product on one line. In this paper, a particular... |
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| SubjectTerms | Algorithms Artificial intelligence Assembly lines Balancing Benders decomposition Business and Management Computational Intelligence Customer satisfaction Customers Decomposition Ergonomics Exact solutions Flexibility Genetic algorithms Image processing systems Lead time Linear programming Management Science Manufacturing Mathematical models Multiple objective analysis Operations Research Operations Research/Decision Theory Original Paper Particle swarm optimization Produce to order Production planning Sorting algorithms Work stations Workloads |
| Title | Benders decomposition algorithm for MMAL balancing problem with express parallel line |
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