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Multiple orders per job batch scheduling with incompatible jobs

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  • Vishnu Erramilli
  • Scott Mason

Abstract

The multiple orders per job (MOJ) scheduling problem is presented for the batch-processing environment such as that exemplified by diffusion ovens. A mixed-integer programming formulation is presented for the incompatible job family case wherein only jobs that belong to the same family may be grouped together in a production batch. This optimization formulation is tested through an extensive experimental design with the objective of minimizing total weighted tardiness (maximizing on-time delivery performance). Optimal solutions are achievable for this initial set of 6-to-12 order problems, but it is noted that the optimization model takes an unreasonable amount of computation time, which suggests the need for heuristic development to support the analysis of larger, more practical MOJ batch scheduling problems. A number of simple heuristic approaches are investigated in an attempt to find near-optimal solutions in a reasonable amount of computation time. It is seen that a combination of the heuristics produces near-optimal solutions for small order problems. Further testing proves that these heuristic combinations are the best for large order problems as well. Copyright Springer Science+Business Media, LLC 2008

Suggested Citation

  • Vishnu Erramilli & Scott Mason, 2008. "Multiple orders per job batch scheduling with incompatible jobs," Annals of Operations Research, Springer, vol. 159(1), pages 245-260, March.
    • Handle: RePEc:spr:annopr:v:159:y:2008:i:1:p:245-260:10.1007/s10479-007-0286-x
    DOI: 10.1007/s10479-007-0286-x
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    References listed on IDEAS

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    1. Gregory Dobson & Ramakrishnan S. Nambimadom, 2001. "The Batch Loading and Scheduling Problem," Operations Research, INFORMS, vol. 49(1), pages 52-65, February.
    2. Javad H. Ahmadi & Reza H. Ahmadi & Sriram Dasu & Christopher S. Tang, 1992. "Batching and Scheduling Jobs on Batch and Discrete Processors," Operations Research, INFORMS, vol. 40(4), pages 750-763, August.
    3. Ari P. J. Vepsalainen & Thomas E. Morton, 1987. "Priority Rules for Job Shops with Weighted Tardiness Costs," Management Science, INFORMS, vol. 33(8), pages 1035-1047, August.
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    Cited by:

    1. Artur Alves Pessoa & Teobaldo Bulhões & Vitor Nesello & Anand Subramanian, 2022. "Exact Approaches for Single Machine Total Weighted Tardiness Batch Scheduling," INFORMS Journal on Computing, INFORMS, vol. 34(3), pages 1512-1530, May.
    2. Oleh Sobeyko & Lars Mönch, 2015. "Grouping genetic algorithms for solving single machine multiple orders per job scheduling problems," Annals of Operations Research, Springer, vol. 235(1), pages 709-739, December.
    3. Mason, Scott J. & Chen, Jen-Shiang, 2010. "Scheduling multiple orders per job in a single machine to minimize total completion time," European Journal of Operational Research, Elsevier, vol. 207(1), pages 70-77, November.
    4. Eduardo Queiroga & Rian G. S. Pinheiro & Quentin Christ & Anand Subramanian & Artur A. Pessoa, 2021. "Iterated local search for single machine total weighted tardiness batch scheduling," Journal of Heuristics, Springer, vol. 27(3), pages 353-438, June.

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