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Joint decision-making for divisional seru scheduling and worker assignment considering process sequence constraints

Author

Listed:
  • Lili Wang

    (Nanjing University)

  • Min Li

    (Nanjing University
    Civil Aviation Flight University of China)

  • Guanbin Kong

    (Nanjing University)

  • Haiwen Xu

    (Civil Aviation Flight University of China)

Abstract

This paper concentrates on the divisional seru scheduling and worker assignment joint decision-making problem, and synthetically considers the difference in workers’ skill sets, the diversity of workers’ skill levels, the process sequence constraints, setup time, lot-splitting, etc., and then a nonlinear integer programming model is constructed to minimize the makespan. We show that it is necessary to consider the process sequence constraints, and the optimal makespan of the worker-operation allocation scheme without considering the process sequence constraints is much larger than that of considering the process sequence constraints. Moreover, as the number of workers increases, the advantage of considering sequence constraints becomes more obvious. Considering the multi-decision attributes and intractable computations of the studied problem, we turn it into bi-level programming. Then based on the combination of a hybrid genetic variable neighbourhood search algorithm (HGVNSA) and a greedy heuristic algorithm (GHA), a bi-level nested heuristic algorithm (HGVNSA-GHA) is designed. Finally, numerical experiment results show that the proposed algorithm can achieve better results and higher efficiency for the divisional seru scheduling and worker assignment model.

Suggested Citation

  • Lili Wang & Min Li & Guanbin Kong & Haiwen Xu, 2024. "Joint decision-making for divisional seru scheduling and worker assignment considering process sequence constraints," Annals of Operations Research, Springer, vol. 338(2), pages 1157-1185, July.
  • Handle: RePEc:spr:annopr:v:338:y:2024:i:2:d:10.1007_s10479-024-05983-w
    DOI: 10.1007/s10479-024-05983-w
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    References listed on IDEAS

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