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A Mathematical Model and a Simulated Annealing Algorithm for Balancing Multi-manned Assembly Line Problem with Sequence-Dependent Setup Time

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  • Wucheng Yang
  • Wenming Cheng

Abstract

Multi-manned assembly lines have been widely applied to the industrial production, especially for large-sized products such as cars, buses, and trucks, in which more than one operator in the same station simultaneously performs different tasks in parallel. This study deals with a multi-manned assembly line balancing problem by simultaneously considering the forward and backward sequence-dependent setup time (MALBPS). A mixed-integer programming is established to characterize the problem. Besides, a simulated annealing algorithm is also proposed to solve it. To validate the performance of the proposed approaches, a set of benchmark instances are tested and the lower bound of the proposed problem is also given. The results demonstrated that the proposed algorithm is quite effective to solve the problem.

Suggested Citation

  • Wucheng Yang & Wenming Cheng, 2020. "A Mathematical Model and a Simulated Annealing Algorithm for Balancing Multi-manned Assembly Line Problem with Sequence-Dependent Setup Time," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-16, May.
    • Handle: RePEc:hin:jnlmpe:8510253
    DOI: 10.1155/2020/8510253
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    Cited by:

    1. Andreu-Casas, Enric & García-Villoria, Alberto & Pastor, Rafael, 2022. "Multi-manned assembly line balancing problem with dependent task times: a heuristic based on solving a partition problem with constraints," European Journal of Operational Research, Elsevier, vol. 302(1), pages 96-116.
    2. Battaïa, Olga & Dolgui, Alexandre, 2022. "Hybridizations in line balancing problems: A comprehensive review on new trends and formulations," International Journal of Production Economics, Elsevier, vol. 250(C).
    3. Mao, Zhaofang & Sun, Yiting & Fang, Kan & Huang, Dian & Zhang, Jiaxin, 2024. "Balancing and scheduling of assembly line with multi-type collaborative robots," International Journal of Production Economics, Elsevier, vol. 271(C).

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