IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v87y1999i0p103-11610.1023-a1018960314433.html
   My bibliography  Save this article

A discrete‐time model for perishable inventory systems

Author

Listed:
  • Z. Lian
  • L. Liu

Abstract

We study a discrete-time (s, S) perishable inventory model with geometric inter‐demand times and batch demands. With a zero lead time and allowing backlogs, we can construct a multi‐dimensional Markov chain to model the inventory‐level process and obtain a closed‐formcost function. Numerical computation for the discrete‐time models is quite manageable. Our numerical results reveal some good properties of the cost function. By comparing our results with results from the corresponding continuous‐time models, we may also conclude that discrete‐time models may be used to approximate their continuous‐time counterparts effectively. Copyright Kluwer Academic Publishers 1999

Suggested Citation

  • Z. Lian & L. Liu, 1999. "A discrete‐time model for perishable inventory systems," Annals of Operations Research, Springer, vol. 87(0), pages 103-116, April.
    • Handle: RePEc:spr:annopr:v:87:y:1999:i:0:p:103-116:10.1023/a:1018960314433
    DOI: 10.1023/A:1018960314433
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1023/A:1018960314433
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1023/A:1018960314433?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. Huanan Zhang & Cong Shi & Xiuli Chao, 2016. "Technical Note—Approximation Algorithms for Perishable Inventory Systems with Setup Costs," Operations Research, INFORMS, vol. 64(2), pages 432-440, April.
    2. Xiang Li & Guohua Sun & Yongjian Li, 2016. "A multi-period ordering and clearance pricing model considering the competition between new and out-of-season products," Annals of Operations Research, Springer, vol. 242(2), pages 207-221, July.
    3. Yves Crama & Mahmood Rezaei & Martin Savelsbergh & Tom Van Woensel, 2018. "Stochastic Inventory Routing for Perishable Products," Transportation Science, INFORMS, vol. 52(3), pages 526-546, June.

    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:87:y:1999:i:0:p:103-116:10.1023/a:1018960314433. 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: 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.