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An efficient branch and bound algorithm for smoothing the workloads on simple assembly lines

Author

Listed:
  • Öncü Hazir

    (ESC [Rennes] - ESC Rennes School of Business)

  • Maher Agi

    (ESC [Rennes] - ESC Rennes School of Business)

  • Jérémy Guérin

    (ESC [Rennes] - ESC Rennes School of Business)

Abstract

In this study, we develop a branch and bound solution algorithm to solve the workload smoothing problem. Our algorithm incorporates new formulas for dynamically computing a lower bound on the optimal value of the objective function and for determining the earliest workstations for tasks. It also uses a fast heuristic for computing a good initial upper bound. A comprehensive experimental analysis is conducted in this study. The analysis demonstrates the outstanding performance of the algorithm and its efficiency in solving medium-sized workload smoothing problems.

Suggested Citation

  • Öncü Hazir & Maher Agi & Jérémy Guérin, 2021. "An efficient branch and bound algorithm for smoothing the workloads on simple assembly lines," Post-Print hal-03160641, HAL.
  • Handle: RePEc:hal:journl:hal-03160641
    DOI: 10.1080/00207543.2019.1701208
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    Citations

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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. 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. Anel, Juan Ignacio & Català, Pau & Serra, Moisès & Domenech, Bruno, 2022. "New Matrix Methodology for Algorithmic Transparency in Assembly Line Balancing Using a Genetic Algorithm," Operations Research Perspectives, Elsevier, vol. 9(C).
    4. Walter, Rico & Schulze, Philipp & Scholl, Armin, 2021. "SALSA: Combining branch-and-bound with dynamic programming to smoothen workloads in simple assembly line balancing," European Journal of Operational Research, Elsevier, vol. 295(3), pages 857-873.

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