IDEAS home Printed from https://ideas.repec.org/a/taf/uiiexx/v41y2009i6p498-510.html
   My bibliography  Save this article

Computing protection level policies for dynamic capacity allocation problems by using stochastic approximation methods

Author

Listed:
  • Alexander Erdelyi
  • Huseyin Topaloglu

Abstract

A dynamic capacity allocation problem is considered in this paper. A fixed amount of daily processing capacity is allowed. Jobs of different priorities arrive randomly over time and a decision is required on which jobs should be scheduled on which days. The jobs that are waiting to be processed incur a holding cost depending on their priority levels. The objective is to minimize the total expected cost over a planning horizon. In this paper the focus is on a class of policies that are characterized by a set of protection levels. The role of the protection levels is to “protect” a portion of the capacity from the lower priority jobs so as to make it available for the future higher priority jobs. A stochastic approximation method to find a good set of protection levels is developed and its convergence is proved. Computational experiments indicate that protection level policies perform especially well when the coefficient of variation for the job arrivals is high.[Supplementary materials are available for this article. Go to the publisher's online edition of IIE Transactions for the following free supplemental resource: Technical appendix detailing the proofs of propositions.]

Suggested Citation

  • Alexander Erdelyi & Huseyin Topaloglu, 2009. "Computing protection level policies for dynamic capacity allocation problems by using stochastic approximation methods," IISE Transactions, Taylor & Francis Journals, vol. 41(6), pages 498-510.
    • Handle: RePEc:taf:uiiexx:v:41:y:2009:i:6:p:498-510
    DOI: 10.1080/07408170802706543
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/07408170802706543
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/07408170802706543?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.

    Citations

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


    Cited by:

    1. Geng, Na & Xie, Xiaolan, 2012. "Optimizing contracted resource capacity with two advance cancelation modes," European Journal of Operational Research, Elsevier, vol. 221(3), pages 501-512.
    2. Amin Khademi & Denis R. Saure & Andrew J. Schaefer & Ronald S. Braithwaite & Mark S. Roberts, 2015. "The Price of Nonabandonment: HIV in Resource-Limited Settings," Manufacturing & Service Operations Management, INFORMS, vol. 17(4), pages 554-570, October.
    3. Hans-Jörg Schütz & Rainer Kolisch, 2013. "Capacity allocation for demand of different customer-product-combinations with cancellations, no-shows, and overbooking when there is a sequential delivery of service," Annals of Operations Research, Springer, vol. 206(1), pages 401-423, July.
    4. Schütz, Hans-Jörg & Kolisch, Rainer, 2012. "Approximate dynamic programming for capacity allocation in the service industry," European Journal of Operational Research, Elsevier, vol. 218(1), pages 239-250.
    5. Xiang Ma & Antoine Sauré & Martin L. Puterman & Marianne Taylor & Scott Tyldesley, 2016. "Capacity planning and appointment scheduling for new patient oncology consults," Health Care Management Science, Springer, vol. 19(4), pages 347-361, December.
    6. Van-Anh Truong, 2015. "Optimal Advance Scheduling," Management Science, INFORMS, vol. 61(7), pages 1584-1597, July.
    7. Na Geng & Letian Chen & Ran Liu & Yanhong Zhu, 2017. "Optimal patient assignment for W queueing network in a diagnostic facility setting," International Journal of Production Research, Taylor & Francis Journals, vol. 55(19), pages 5609-5631, October.
    8. Ahmadi-Javid, Amir & Jalali, Zahra & Klassen, Kenneth J, 2017. "Outpatient appointment systems in healthcare: A review of optimization studies," European Journal of Operational Research, Elsevier, vol. 258(1), pages 3-34.
    9. Antoine Sauré & Martin L. Puterman, 2014. "The Appointment Scheduling Game," INFORMS Transactions on Education, INFORMS, vol. 14(2), pages 73-85, February.
    10. Ting-Yu Ho & Shan Liu & Zelda B. Zabinsky, 2019. "A Multi-Fidelity Rollout Algorithm for Dynamic Resource Allocation in Population Disease Management," Health Care Management Science, Springer, vol. 22(4), pages 727-755, December.
    11. Astaraky, Davood & Patrick, Jonathan, 2015. "A simulation based approximate dynamic programming approach to multi-class, multi-resource surgical scheduling," European Journal of Operational Research, Elsevier, vol. 245(1), pages 309-319.
    12. Antoine Sauré & Jonathan Patrick & Martin L. Puterman, 2015. "Simulation-Based Approximate Policy Iteration with Generalized Logistic Functions," INFORMS Journal on Computing, INFORMS, vol. 27(3), pages 579-595, August.
    13. Sauré, Antoine & Patrick, Jonathan & Tyldesley, Scott & Puterman, Martin L., 2012. "Dynamic multi-appointment patient scheduling for radiation therapy," European Journal of Operational Research, Elsevier, vol. 223(2), pages 573-584.
    14. Geng, Na & Xie, Xiaolan & Jiang, Zhibin, 2013. "Implementation strategies of a contract-based MRI examination reservation process for stroke patients," European Journal of Operational Research, Elsevier, vol. 231(2), pages 371-380.

    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:taf:uiiexx:v:41:y:2009:i:6:p:498-510. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/uiie .

    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.