IDEAS home Printed from https://ideas.repec.org/a/inm/ormoor/v49y2024i2p928-947.html
   My bibliography  Save this article

Minimization Fractional Prophet Inequalities for Sequential Procurement

Author

Listed:
  • Junjie Qin

    (Purdue University, West Lafayette, Indiana 47907)

  • Shai Vardi

    (Purdue University, West Lafayette, Indiana 47907)

  • Adam Wierman

    (California Institute of Technology, Pasadena, California 91125)

Abstract

We consider a minimization variant on the classical prophet inequality with monomial cost functions. A firm would like to procure some fixed amount of a divisible commodity from sellers that arrive sequentially. Whenever a seller arrives, the seller’s cost function is revealed, and the firm chooses how much of the commodity to buy. We first show that if one restricts the set of distributions for the coefficients to a family of natural distributions that include, for example, the uniform and truncated normal distributions, then there is a thresholding policy that is asymptotically optimal in the number of sellers. We then compare two scenarios based on whether the firm has in-house production capabilities or not. We precisely compute the optimal algorithm’s competitive ratio when in-house production capabilities exist and for a special case when they do not. We show that the main advantage of the ability to produce the commodity in house is that it shields the firm from price spikes in worst-case scenarios.

Suggested Citation

  • Junjie Qin & Shai Vardi & Adam Wierman, 2024. "Minimization Fractional Prophet Inequalities for Sequential Procurement," Mathematics of Operations Research, INFORMS, vol. 49(2), pages 928-947, May.
  • Handle: RePEc:inm:ormoor:v:49:y:2024:i:2:p:928-947
    DOI: 10.1287/moor.2021.0173
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/moor.2021.0173
    Download Restriction: no

    File URL: https://libkey.io/10.1287/moor.2021.0173?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:ormoor:v:49:y:2024:i:2:p:928-947. 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.