IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v16y1970i8pb533-b548.html
   My bibliography  Save this article

Adaptive Limits in Inventory Control

Author

Listed:
  • Samuel Eilon

    (Imperial College of Science and Technology)

  • Joseph Elmaleh

    (Imperial College of Science and Technology)

Abstract

In conventional reorder policies for inventory control, stocks are allowed to fluctuate between two prescribed limits: a lower limit corresponding to a safety stock to guard against runouts, and an upper limit to which the stock is replenished from time to time. Methods have been suggested for computing optimal upper and lower limits for the case of stationary demand patterns. The adoption of two rigid limits for controlling inventories for nonstationary demand patterns, which include trends and seasonal fluctuations, is clearly not satisfactory. Published papers in inventory control rarely devote enough attention to the need for a link between forecasting and a reorder policy. A method is suggested in this paper for computing adaptive control limits based on a forecasting procedure that takes account of seasonal fluctuations and trends. The method has been simulated for inventory models with varying parameters. Invariably it has yielded results which were equal to and usually better than those obtained by the optimal "fixed-limits" method. For example, in the case of a normal demand distribution, and a given level of satisfying demand, the reduction in costs resulting from the adaptive control procedure was found to be well over 30%.

Suggested Citation

  • Samuel Eilon & Joseph Elmaleh, 1970. "Adaptive Limits in Inventory Control," Management Science, INFORMS, vol. 16(8), pages 533-548, April.
    • Handle: RePEc:inm:ormnsc:v:16:y:1970:i:8:p:b533-b548
    DOI: 10.1287/mnsc.16.8.B533
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.16.8.B533
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.16.8.B533?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. Pantazopoulos, Sotiris N. & Pappis, Costas P., 1996. "A new adaptive method for extrapolative forecasting algorithms," European Journal of Operational Research, Elsevier, vol. 94(1), pages 106-111, October.
    2. Montanari, Roberto & Bottani, Eleonora & Shekarian, Ehsan & Kazemi, Nima, 2017. "A model for the analysis of procurement strategies in the economic order interval environment," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 134(C), pages 79-98.

    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:16:y:1970:i:8:p:b533-b548. 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.