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The just-in-time job-shop scheduling problem with distinct due-dates for operations

Author

Listed:
  • Mohammad Mahdi Ahmadian

    (University of Technology Sydney)

  • Amir Salehipour

    (University of Technology Sydney)

Abstract

In the just-in-time job-shop scheduling (JIT–JSS) problem every operation has a distinct due-date, and earliness and tardiness penalties. Any deviation from the due-date incurs penalties. The objective of JIT–JSS is to obtain a schedule, i.e., the completion time for performing the operations, with the smallest total (weighted) earliness and tardiness penalties. This paper presents a matheuristic algorithm for the JIT–JSS problem, which operates by decomposing the problem into smaller sub-problems, optimizing the sub-problems and delivering the optimal schedule for the problem. By solving a set of 72 benchmark instances ranging from 10 to 20 jobs and 20 to 200 operations we show that the proposed algorithm outperforms the state-of-the-art methods and the solver CPLEX, and obtains new best solutions for nearly 56% of the instances, including for 79% of the large instances with 20 jobs.

Suggested Citation

  • Mohammad Mahdi Ahmadian & Amir Salehipour, 2021. "The just-in-time job-shop scheduling problem with distinct due-dates for operations," Journal of Heuristics, Springer, vol. 27(1), pages 175-204, April.
    • Handle: RePEc:spr:joheur:v:27:y:2021:i:1:d:10.1007_s10732-020-09458-6
    DOI: 10.1007/s10732-020-09458-6
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    References listed on IDEAS

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    1. Quang Chieu Ta & Jean-Charles Billaut & Jean-Louis Bouquard, 2018. "Matheuristic algorithms for minimizing total tardiness in the m-machine flow-shop scheduling problem," Journal of Intelligent Manufacturing, Springer, vol. 29(3), pages 617-628, March.
    2. David Applegate & William Cook, 1991. "A Computational Study of the Job-Shop Scheduling Problem," INFORMS Journal on Computing, INFORMS, vol. 3(2), pages 149-156, May.
    3. Yvan Dumas & François Soumis & Jacques Desrosiers, 1990. "Technical Note—Optimizing the Schedule for a Fixed Vehicle Path with Convex Inconvenience Costs," Transportation Science, INFORMS, vol. 24(2), pages 145-152, May.
    4. Monch, Lars & Schabacker, Rene & Pabst, Detlef & Fowler, John W., 2007. "Genetic algorithm-based subproblem solution procedures for a modified shifting bottleneck heuristic for complex job shops," European Journal of Operational Research, Elsevier, vol. 177(3), pages 2100-2118, March.
    5. M. R. Garey & D. S. Johnson & Ravi Sethi, 1976. "The Complexity of Flowshop and Jobshop Scheduling," Mathematics of Operations Research, INFORMS, vol. 1(2), pages 117-129, May.
    6. Emine Akyol Ozer & Tugba Sarac, 2019. "MIP models and a matheuristic algorithm for an identical parallel machine scheduling problem under multiple copies of shared resources constraints," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(1), pages 94-124, April.
    7. J. Beck & Philippe Refalo, 2003. "A Hybrid Approach to Scheduling with Earliness and Tardiness Costs," Annals of Operations Research, Springer, vol. 118(1), pages 49-71, February.
    8. Joseph Adams & Egon Balas & Daniel Zawack, 1988. "The Shifting Bottleneck Procedure for Job Shop Scheduling," Management Science, INFORMS, vol. 34(3), pages 391-401, March.
    9. Doi, Tsubasa & Nishi, Tatsushi & Voß, Stefan, 2018. "Two-level decomposition-based matheuristic for airline crew rostering problems with fair working time," European Journal of Operational Research, Elsevier, vol. 267(2), pages 428-438.
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