IDEAS home Printed from https://ideas.repec.org/a/spr/jcomop/v46y2023i1d10.1007_s10878-023-01067-w.html
   My bibliography  Save this article

A combinatorial approximation algorithm for k-level facility location problem with submodular penalties

Author

Listed:
  • Li Zhang

    (Hunan Normal University)

  • Jing Yuan

    (Hunan Normal University)

  • Zhizhen Xu

    (Hunan Normal University)

  • Qiaoliang Li

    (Hunan Normal University)

Abstract

We present an improved approximation algorithm for k-level facility location problem with submodular penalties, the new approximation ratio is 2.9444 for any constant k, which improves the current best approximation ratio 3.314. The central ideas in our results are as follows: first, we restructure the problem as an uncapacitated facility location problem, then we use the primal-dual scheme with greedy augmentation. The key technique of our result is that we change the way of last opening facility set in primal-dual approximation algorithm to get much more tight result for k-level facility location problem with submodular penalties.

Suggested Citation

  • Li Zhang & Jing Yuan & Zhizhen Xu & Qiaoliang Li, 2023. "A combinatorial approximation algorithm for k-level facility location problem with submodular penalties," Journal of Combinatorial Optimization, Springer, vol. 46(1), pages 1-19, August.
  • Handle: RePEc:spr:jcomop:v:46:y:2023:i:1:d:10.1007_s10878-023-01067-w
    DOI: 10.1007/s10878-023-01067-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10878-023-01067-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10878-023-01067-w?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yishui Wang & Dachuan Xu & Donglei Du & Chenchen Wu, 2018. "An approximation algorithm for k-facility location problem with linear penalties using local search scheme," Journal of Combinatorial Optimization, Springer, vol. 36(1), pages 264-279, July.
    2. Guang Xu & Jinhui Xu, 2009. "An improved approximation algorithm for uncapacitated facility location problem with penalties," Journal of Combinatorial Optimization, Springer, vol. 17(4), pages 424-436, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Schnepper, Teresa & Klamroth, Kathrin & Stiglmayr, Michael & Puerto, Justo, 2019. "Exact algorithms for handling outliers in center location problems on networks using k-max functions," European Journal of Operational Research, Elsevier, vol. 273(2), pages 441-451.
    2. Kuzbakov, Yerlan & Ljubić, Ivana, 2024. "New formulations for two location problems with interconnected facilities," European Journal of Operational Research, Elsevier, vol. 314(1), pages 51-65.
    3. Adam N. Elmachtoub & Retsef Levi, 2016. "Supply Chain Management with Online Customer Selection," Operations Research, INFORMS, vol. 64(2), pages 458-473, April.
    4. Yicheng Xu & Dachuan Xu & Donglei Du & Chenchen Wu, 2017. "Local search algorithm for universal facility location problem with linear penalties," Journal of Global Optimization, Springer, vol. 67(1), pages 367-378, January.

    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:jcomop:v:46:y:2023:i:1:d:10.1007_s10878-023-01067-w. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc 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 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.