IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v12y1966i7p517-529.html
   My bibliography  Save this article

A Min-Max Inventory Model

Author

Listed:
  • Norman Agin

    (Columbia University and MATHEMATICA)

Abstract

An inventory model is considered where every N periods an order is placed for an amount which brings the sum of stock-on-hand plus on-order up to some level S. The model treats a single item for which there is random demand. Demands that arrive when there is no positive inventory on hand are back-ordered. Leadtime is treated as random and the receipts of orders are allowed to cross in time. Values N* and S* which minimize steady state expected costs per unit time cannot be found. In this paper approximations, N 0 and S 0 are found. These are determined by minimizing an expected cost per unit time which has been maximized over all distributions of stock deficit with a given mean and variance. The method is applicable even when the functional form of the distribution of demand is not known. Computer simulations are used to indicate the values of the input parameters for which the expected costs per unit time associated with N 0 and S 0 are close to the similar quantities for N* and S*.

Suggested Citation

  • Norman Agin, 1966. "A Min-Max Inventory Model," Management Science, INFORMS, vol. 12(7), pages 517-529, March.
    • Handle: RePEc:inm:ormnsc:v:12:y:1966:i:7:p:517-529
    DOI: 10.1287/mnsc.12.7.517
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.12.7.517
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.12.7.517?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
    ---><---

    Citations

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


    Cited by:

    1. Chatfield, Dean C. & Pritchard, Alan M., 2018. "Crossover aware base stock decisions for service-driven systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 312-330.
    2. Hayya, Jack C. & Bagchi, Uttarayan & Kim, Jeon G. & Sun, Daewon, 2008. "On static stochastic order crossover," International Journal of Production Economics, Elsevier, vol. 114(1), pages 404-413, July.
    3. Hayya, Jack C. & Bagchi, Uttarayan & Ramasesh, Ranga, 2011. "Cost relationships in stochastic inventory systems: A simulation study of the (S, S-1, t=1) model," International Journal of Production Economics, Elsevier, vol. 130(2), pages 196-202, April.
    4. Wang, Xun & Disney, Stephen M., 2017. "Mitigating variance amplification under stochastic lead-time: The proportional control approach," European Journal of Operational Research, Elsevier, vol. 256(1), pages 151-162.

    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:inm:ormnsc:v:12:y:1966:i:7:p:517-529. 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.