IDEAS home Printed from https://ideas.repec.org/a/inm/ormsom/v27y2025i4p1107-1125.html
   My bibliography  Save this article

Capacity Rationing in Multiserver, Nonpreemptive Priority Queues

Author

Listed:
  • Opher Baron

    (Rotman School of Management, University of Toronto, Toronto, Ontario M5S 3E6, Canada)

  • Tianshu Lu

    (Rotman School of Management, University of Toronto, Toronto, Ontario M5S 3E6, Canada)

  • Jianfu Wang

    (College of Business, City University of Hong Kong, Hong Kong)

Abstract

Problem definition : Many service and manufacturing systems use both capacity rationing (CR) and priority to differentiate among their customers. We model these as a two-class nonpreemptive priority M / M / c queueing model and the practice of CR; an arriving low-priority customer can directly enter service only when the number of idle servers is higher than the CR level, k . For these systems, we separately discuss two important features that are common in practice but ignored in the literature; supply is narrowly matched with demand, and service rates are heterogeneous, reflecting different customer types. Methodology and results : When the service times of both classes are identical, our asymptotic results indicate that for a system with a large number of servers, the nondegenerative CR level does not exceed O ( c ) . When the service times of classes differ, we derive exact solutions for different performance measures of interest using queueing and Markov chain decomposition. We numerically demonstrate the impact of system parameters on these performance measures and provide insights on the CR level. Management implications : We show that as predicted by the asymptotic analysis, an O ( c ) CR level can significantly reduce the waits of high-priority customers with little effect on low-priority customers’ waiting. We establish that this insight is robust to heterogeneous service times across classes and other system parameters, such as the number of servers and the arrival rates of the classes.

Suggested Citation

  • Opher Baron & Tianshu Lu & Jianfu Wang, 2025. "Capacity Rationing in Multiserver, Nonpreemptive Priority Queues," Manufacturing & Service Operations Management, INFORMS, vol. 27(4), pages 1107-1125, July.
  • Handle: RePEc:inm:ormsom:v:27:y:2025:i:4:p:1107-1125
    DOI: 10.1287/msom.2021.0106
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/msom.2021.0106
    Download Restriction: no

    File URL: https://libkey.io/10.1287/msom.2021.0106?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
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:inm:ormsom:v:27:y:2025:i:4:p:1107-1125. 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 Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.