IDEAS home Printed from https://ideas.repec.org/a/ids/ijores/v5y2009i1p89-109.html
   My bibliography  Save this article

Hybrid algorithms for the Multiple-choice Multi-dimensional Knapsack Problem

Author

Listed:
  • Nawal Cherfi
  • Mhand Hifi

Abstract

In this paper, we propose three versions of an algorithm for approximately solving large-scale Multiple-choice Multi-dimensional Knapsack Problems (MMKP). First, an adaptation of the local branching is proposed. Second, a hybrid solution procedure is presented that is based on two complementary solution procedures: a local branching which cooperates with a column generation solution procedure. Third and last, an augmented algorithm of the last hybrid algorithm is developed. It can also be viewed as a special truncated branch and bound in which the first hybrid algorithm is applied to a subset of elite nodes generated according to some variables/constraint branchings. The proposed methods are analysed computationally on a set of instances of the literature and compared to the results provided by other algorithms of the literature. Encouraging results have been obtained.

Suggested Citation

  • Nawal Cherfi & Mhand Hifi, 2009. "Hybrid algorithms for the Multiple-choice Multi-dimensional Knapsack Problem," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 5(1), pages 89-109.
    • Handle: RePEc:ids:ijores:v:5:y:2009:i:1:p:89-109
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=24531
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chen, Yuning & Hao, Jin-Kao, 2014. "A “reduce and solve” approach for the multiple-choice multidimensional knapsack problem," European Journal of Operational Research, Elsevier, vol. 239(2), pages 313-322.
    2. Gao, Chao & Lu, Guanzhou & Yao, Xin & Li, Jinlong, 2017. "An iterative pseudo-gap enumeration approach for the Multidimensional Multiple-choice Knapsack Problem," European Journal of Operational Research, Elsevier, vol. 260(1), pages 1-11.
    3. Jaeyoung Yang & Yong-Hyuk Kim & Yourim Yoon, 2022. "A Memetic Algorithm with a Novel Repair Heuristic for the Multiple-Choice Multidimensional Knapsack Problem," Mathematics, MDPI, vol. 10(4), pages 1-15, February.

    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:ids:ijores:v:5:y:2009:i:1:p:89-109. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=170 .

    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.