IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this paper

Derivation of confidence intervals of service measures in a base-stock inventory control system with low-frequent demand

Listed author(s):
Registered author(s):

    We explore a base-stock system with backlogging where the demand process is a compound renewal process and the compound element is a delayed geometric distribution. For this setting it is proven in [4] that the long-run average service measures order fill rate (OFR) and volume fill rate (VFR) are equal in values. In [4] it is also demonstrated that although equal ex ante one will ex post observe differences as actual sample paths are different. By including a low-frequency assumption in the model, we are able to derive mathematical expressions of the confidence intervals one will get if OFR and VFR are estimated in a simulation using the regenerative method. Through numerical examples we show that of the two service measures it is OFR that can be estimated most accurately. However, simulation results show that the opposite conclusion holds if we instead consider finitehorizon service measures, namely per-cycle variants of OFR and VFR.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL:
    Download Restriction: no

    Paper provided by University of Aarhus, Aarhus School of Business, Department of Business Studies in its series CORAL Working Papers with number L-2008-03.

    in new window

    Length: 20 pages
    Date of creation: 01 Jan 2008
    Handle: RePEc:hhb:aarbls:2008-003
    Contact details of provider: Postal:
    The Aarhus School of Business, Fuglesangs Allé 4, DK-8210 Aarhus V, Denmark

    Fax: + 45 86 15 19 43
    Web page:

    More information through EDIRC

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    in new window

    1. J. B. Ward, 1978. "Determining Reorder Points When Demand is Lumpy," Management Science, INFORMS, vol. 24(6), pages 623-632, February.
    2. Douglas J. Thomas, 2005. "Measuring Item Fill-Rate Performance in a Finite Horizon," Manufacturing & Service Operations Management, INFORMS, vol. 7(1), pages 74-80, September.
    3. Chen, Frank Y. & Krass, Dmitry, 2001. "Inventory models with minimal service level constraints," European Journal of Operational Research, Elsevier, vol. 134(1), pages 120-140, October.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:hhb:aarbls:2008-003. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Helle Vinbaek Stenholt)

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.