IDEAS home Printed from https://ideas.repec.org/h/spr/lnopch/978-3-031-24907-5_7.html
   My bibliography  Save this book chapter

The Stochastic Bilevel Selection Problem

In: Operations Research Proceedings 2022

Author

Listed:
  • Jannik Irmai

    (TU Dresden)

Abstract

We consider a bilevel continuous knapsack problem where the leader controls the capacity of the knapsack, while the follower chooses a feasible packing maximizing his own profit. The leader’s aim is to optimize a linear objective function in the follower’s solution, but with respect to item values that can be different from the follower’s item values. We address a stochastic version of this problem where the follower’s profits are uncertain and only a probability distribution is known. This problem is #P-hard for the case of independently and uniformly distributed follower profits. In this paper, efficient algorithms are developed for the special case where all items have unit weight, as is the case in the bilevel selection problem. Generalizing these results to the case of arbitrary weights leads to pseudo-polynomial time algorithms for the bilevel continuous knapsack problem.

Suggested Citation

  • Jannik Irmai, 2023. "The Stochastic Bilevel Selection Problem," Lecture Notes in Operations Research, in: Oliver Grothe & Stefan Nickel & Steffen Rebennack & Oliver Stein (ed.), Operations Research Proceedings 2022, chapter 0, pages 51-57, Springer.
  • Handle: RePEc:spr:lnopch:978-3-031-24907-5_7
    DOI: 10.1007/978-3-031-24907-5_7
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:lnopch:978-3-031-24907-5_7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.