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A hybrid adaptive variable neighbourhood search approach for multi-sided assembly line balancing problem to minimise the cycle time

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  • Abdolreza Roshani
  • Massimo Paolucci
  • Davide Giglio
  • Flavio Tonelli

Abstract

Multi-sided assembly line balancing problems usually occur in plants producing big-sized products such as buses, trucks, and helicopters. In this type of assembly line, in each workstation, it is possible to install several workplaces, in which a single operator performs his/her own set of tasks at an individual mounting position. In this way, the operators can work simultaneously on the same product without hindering each other. This paper considers for the first time the multi-sided assembly line balancing problem with the objective of minimising the cycle time, proposing a new mathematical formulation to solve small-sized instances of this problem. Besides, a metaheuristic algorithm based on variable neighbourhood search hybridised with simulated annealing is developed to solve large-sized instances. The algorithm is called adaptive because of the adopted neighbourhood selection mechanism. A novel three-string representation is introduced to encode the problem solutions and six different neighbourhood generation structures are presented. The developed approach is compared to other meta-heuristics, considering some well-known in literature test instance and a real world assembly line balancing problem arising in a car body assembly line. The experimental results validate the effectiveness of the proposed algorithm.

Suggested Citation

  • Abdolreza Roshani & Massimo Paolucci & Davide Giglio & Flavio Tonelli, 2021. "A hybrid adaptive variable neighbourhood search approach for multi-sided assembly line balancing problem to minimise the cycle time," International Journal of Production Research, Taylor & Francis Journals, vol. 59(12), pages 3696-3721, June.
    • Handle: RePEc:taf:tprsxx:v:59:y:2021:i:12:p:3696-3721
    DOI: 10.1080/00207543.2020.1749958
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    Cited by:

    1. Boysen, Nils & Schulze, Philipp & Scholl, Armin, 2022. "Assembly line balancing: What happened in the last fifteen years?," European Journal of Operational Research, Elsevier, vol. 301(3), pages 797-814.
    2. Yang, Xuan & Kong, Xiang T.R. & Huang, George Q., 2024. "Synchronizing crowdsourced co-modality between passenger and freight transportation services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
    3. 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).
    4. Eduardo Álvarez-Miranda & Jordi Pereira & Harold Torrez-Meruvia & Mariona Vilà, 2021. "A Hybrid Genetic Algorithm for the Simple Assembly Line Balancing Problem with a Fixed Number of Workstations," Mathematics, MDPI, vol. 9(17), pages 1-19, September.

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