IDEAS home Printed from https://ideas.repec.org/a/spr/queues/v100y2022i3d10.1007_s11134-022-09794-3.html
   My bibliography  Save this article

A load-balancing problem for distributed bulk-service queues with size-dependent batch processing times

Author

Listed:
  • Yoshiaki Inoue

    (Osaka University)

Abstract

No abstract is available for this item.

Suggested Citation

  • Yoshiaki Inoue, 2022. "A load-balancing problem for distributed bulk-service queues with size-dependent batch processing times," Queueing Systems: Theory and Applications, Springer, vol. 100(3), pages 449-451, April.
  • Handle: RePEc:spr:queues:v:100:y:2022:i:3:d:10.1007_s11134-022-09794-3
    DOI: 10.1007/s11134-022-09794-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11134-022-09794-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11134-022-09794-3?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. Samuli Aalto, 2000. "Optimal control of batch service queues with finite service capacity and linear holding costs," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 51(2), pages 263-285, April.
    2. Papadaki, Katerina P. & Powell, Warren B., 2002. "Exploiting structure in adaptive dynamic programming algorithms for a stochastic batch service problem," European Journal of Operational Research, Elsevier, vol. 142(1), pages 108-127, October.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    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. De Munck, Thomas & Chevalier, Philippe & Tancrez, Jean-Sébastien, 2023. "Managing priorities on on-demand service platforms with waiting time differentiation," International Journal of Production Economics, Elsevier, vol. 266(C).
    2. Jianxin Fang & Brenda Cheang & Andrew Lim, 2023. "Problems and Solution Methods of Machine Scheduling in Semiconductor Manufacturing Operations: A Survey," Sustainability, MDPI, vol. 15(17), pages 1-44, August.
    3. Satır, Benhür & Erenay, Fatih Safa & Bookbinder, James H., 2018. "Shipment consolidation with two demand classes: Rationing the dispatch capacity," European Journal of Operational Research, Elsevier, vol. 270(1), pages 171-184.
    4. 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.
    5. Ou, Jinwen & Lu, Lingfa & Zhong, Xueling, 2023. "Parallel-batch scheduling with rejection: Structural properties and approximation algorithms," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1017-1032.
    6. Daniel R. Jiang & Warren B. Powell, 2015. "An Approximate Dynamic Programming Algorithm for Monotone Value Functions," Operations Research, INFORMS, vol. 63(6), pages 1489-1511, December.
    7. Lin, Ran & Wang, Jun-Qiang & Liu, Zhixin & Xu, Jun, 2023. "Best possible algorithms for online scheduling on identical batch machines with periodic pulse interruptions," European Journal of Operational Research, Elsevier, vol. 309(1), pages 53-64.
    8. Lin, Ran & Wang, Jun-Qiang & Oulamara, Ammar, 2023. "Online scheduling on parallel-batch machines with periodic availability constraints and job delivery," Omega, Elsevier, vol. 116(C).
    9. Haskilic, Volkan & Ulucan, Aydin & Atici, Kazim Baris & Sarac, Seda Busra, 2023. "A real-world case of autoclave loading and scheduling problems in aerospace composite material production," Omega, Elsevier, vol. 120(C).
    10. Jan-Kees Ommeren & Niek Baer & Nishant Mishra & Debjit Roy, 2020. "Batch service systems with heterogeneous servers," Queueing Systems: Theory and Applications, Springer, vol. 95(3), pages 251-269, August.
    11. Dall'Orto, Leonardo Campo & Crainic, Teodor Gabriel & Leal, Jose Eugenio & Powell, Warren B., 2006. "The single-node dynamic service scheduling and dispatching problem," European Journal of Operational Research, Elsevier, vol. 170(1), pages 1-23, April.
    12. Ulmer, Marlin W. & Thomas, Barrett W., 2020. "Meso-parametric value function approximation for dynamic customer acceptances in delivery routing," European Journal of Operational Research, Elsevier, vol. 285(1), pages 183-195.
    13. Yongpei Guan & Andrew J. Miller, 2008. "Polynomial-Time Algorithms for Stochastic Uncapacitated Lot-Sizing Problems," Operations Research, INFORMS, vol. 56(5), pages 1172-1183, October.
    14. Tian, Zheng & Zheng, Li, 2024. "Single machine parallel-batch scheduling under time-of-use electricity prices: New formulations and optimisation approaches," European Journal of Operational Research, Elsevier, vol. 312(2), pages 512-524.
    15. Xia Qian & Zhang Xingong, 2023. "Online scheduling of two-machine flowshop with lookahead and incompatible job families," Journal of Combinatorial Optimization, Springer, vol. 45(1), pages 1-11, January.
    16. Sumit Kunnumkal & Huseyin Topaloglu, 2008. "Exploiting the Structural Properties of the Underlying Markov Decision Problem in the Q-Learning Algorithm," INFORMS Journal on Computing, INFORMS, vol. 20(2), pages 288-301, May.
    17. Wang, Yi & Zhang, Sheng Hao, 2021. "Optimal production and inventory rationing policies with selective-information sharing and two demand classes," European Journal of Operational Research, Elsevier, vol. 288(2), pages 394-407.
    18. Zhang, Han & Li, Kai & Jia, Zhao-hong & Chu, Chengbin, 2023. "Minimizing total completion time on non-identical parallel batch machines with arbitrary release times using ant colony optimization," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1024-1046.
    19. Toriello, Alejandro & Vielma, Juan Pablo, 2012. "Fitting piecewise linear continuous functions," European Journal of Operational Research, Elsevier, vol. 219(1), pages 86-95.

    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:queues:v:100:y:2022:i:3:d:10.1007_s11134-022-09794-3. 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.