IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v159y2008i1p245-26010.1007-s10479-007-0286-x.html
   My bibliography  Save this article

Multiple orders per job batch scheduling with incompatible jobs

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-007-0286-x
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-007-0286-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Gregory Dobson & Ramakrishnan S. Nambimadom, 2001. "The Batch Loading and Scheduling Problem," Operations Research, INFORMS, vol. 49(1), pages 52-65, February.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fowler, John W. & Mönch, Lars, 2022. "A survey of scheduling with parallel batch (p-batch) processing," European Journal of Operational Research, Elsevier, vol. 298(1), pages 1-24.
    2. Koh, Shie-Gheun & Koo, Pyung-Hoi & Kim, Dong-Chun & Hur, Won-Suk, 2005. "Scheduling a single batch processing machine with arbitrary job sizes and incompatible job families," International Journal of Production Economics, Elsevier, vol. 98(1), pages 81-96, October.
    3. Laub, Jeffrey D. & Fowler, John W. & Keha, Ahmet B., 2007. "Minimizing makespan with multiple-orders-per-job in a two-machine flowshop," European Journal of Operational Research, Elsevier, vol. 182(1), pages 63-79, October.
    4. Thomas Schmitt & Bruce Faaland, 2004. "Scheduling recurrent construction," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(8), pages 1102-1128, December.
    5. Sun Lee, Ik & Yoon, S.H., 2010. "Coordinated scheduling of production and delivery stages with stage-dependent inventory holding costs," Omega, Elsevier, vol. 38(6), pages 509-521, December.
    6. Alidaee, Bahram & Kochenberger, Gary A. & Amini, Mohammad M., 2001. "Greedy solutions of selection and ordering problems," European Journal of Operational Research, Elsevier, vol. 134(1), pages 203-215, October.
    7. S. David Wu & Eui-Seok Byeon & Robert H. Storer, 1999. "A Graph-Theoretic Decomposition of the Job Shop Scheduling Problem to Achieve Scheduling Robustness," Operations Research, INFORMS, vol. 47(1), pages 113-124, February.
    8. Chakhlevitch, Konstantin & Glass, Celia A. & Kellerer, Hans, 2011. "Batch machine production with perishability time windows and limited batch size," European Journal of Operational Research, Elsevier, vol. 210(1), pages 39-47, April.
    9. Bierwirth, C. & Kuhpfahl, J., 2017. "Extended GRASP for the job shop scheduling problem with total weighted tardiness objective," European Journal of Operational Research, Elsevier, vol. 261(3), pages 835-848.
    10. S-W Lin & K-C Ying, 2008. "A hybrid approach for single-machine tardiness problems with sequence-dependent setup times," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(8), pages 1109-1119, August.
    11. M. Vimala Rani & M. Mathirajan, 2020. "Performance evaluation of due-date based dispatching rules in dynamic scheduling of diffusion furnace," OPSEARCH, Springer;Operational Research Society of India, vol. 57(2), pages 462-512, June.
    12. Yuan, Jinjiang & Soukhal, Ameur & Chen, Youjun & Lu, Lingfa, 2007. "A note on the complexity of flow shop scheduling with transportation constraints," European Journal of Operational Research, Elsevier, vol. 178(3), pages 918-925, May.
    13. Christoph Hertrich & Christian Weiß & Heiner Ackermann & Sandy Heydrich & Sven O. Krumke, 2022. "Online algorithms to schedule a proportionate flexible flow shop of batching machines," Journal of Scheduling, Springer, vol. 25(6), pages 643-657, December.
    14. Maria Anna Huka & Christian Rindler & Manfred Gronalt, 2021. "Scheduling and loading problem for multiple, identical dry kilns," Flexible Services and Manufacturing Journal, Springer, vol. 33(2), pages 312-336, June.
    15. Ruyan Fu & Ji Tian & Shisheng Li & Jinjiang Yuan, 2017. "An optimal online algorithm for the parallel-batch scheduling with job processing time compatibilities," Journal of Combinatorial Optimization, Springer, vol. 34(4), pages 1187-1197, November.
    16. Mattfeld, Dirk C. & Bierwirth, Christian, 2004. "An efficient genetic algorithm for job shop scheduling with tardiness objectives," European Journal of Operational Research, Elsevier, vol. 155(3), pages 616-630, June.
    17. Valente, Jorge M.S., 2007. "Improving the performance of the ATC dispatch rule by using workload data to determine the lookahead parameter value," International Journal of Production Economics, Elsevier, vol. 106(2), pages 563-573, April.
    18. Chang, Yung-Chia & Lee, Chung-Yee, 2004. "Machine scheduling with job delivery coordination," European Journal of Operational Research, Elsevier, vol. 158(2), pages 470-487, October.
    19. Ciftci, B.B. & Borm, P.E.M. & Hamers, H.J.M. & Slikker, M., 2008. "Batch Sequencing and Cooperation," Other publications TiSEM ed1f8fce-da76-41a6-9a9e-9, Tilburg University, School of Economics and Management.
    20. Julia Lange & Frank Werner, 2018. "Approaches to modeling train scheduling problems as job-shop problems with blocking constraints," Journal of Scheduling, Springer, vol. 21(2), pages 191-207, April.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:159:y:2008:i:1:p:245-260:10.1007/s10479-007-0286-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.