IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v31y1985i9p1150-1160.html
   My bibliography  Save this article

Bayes Solution to Dynamic Inventory Models Under Unknown Demand Distribution

Author

Listed:
  • Katy S. Azoury

    (School of Business Administration and Economics, California State University, Northridge, California 91330)

Abstract

This paper considers the periodic review inventory problem for which one or more parameters of the demand distribution are unknown with a known prior distribution chosen from the natural conjugate family. The Bayesian formulation of this problem results in a dynamic program with a multi-dimensional state space. Two models are analysed: the depletive inventory model of consumable items and the nondepletive model of reparable items. For both models and for some specific demand distributions, it is shown that the solution of the Bayesian model can be reduced to that of solving another dynamic program with a one-dimensional state space. Moreover, an explicit form for the optimal Bayesian ordering policy is given in each case.

Suggested Citation

  • Katy S. Azoury, 1985. "Bayes Solution to Dynamic Inventory Models Under Unknown Demand Distribution," Management Science, INFORMS, vol. 31(9), pages 1150-1160, September.
    • Handle: RePEc:inm:ormnsc:v:31:y:1985:i:9:p:1150-1160
    DOI: 10.1287/mnsc.31.9.1150
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.31.9.1150
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.31.9.1150?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
    ---><---

    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:ormnsc:v:31:y:1985:i:9:p:1150-1160. 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.