IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-642-38189-8_11.html
   My bibliography  Save this book chapter

The Maximum Weight Connected Subgraph Problem

In: Facets of Combinatorial Optimization

Author

Listed:
  • Eduardo Álvarez-Miranda

    (Università di Bologna, Dipartimento di Ingegneria dell’Energia Elettrica e dell’Informazione)

  • Ivana Ljubić

    (Universität Wien, Institut für Statistik und Operations Research)

  • Petra Mutzel

    (Technische Universität Dortmund, Fakultät für Informatik)

Abstract

The Maximum (Node-) Weight Connected Subgraph Problem (MWCS) searches for a connected subgraph with maximum total weight in a node-weighted (di)graph. In this work we introduce a new integer linear programming formulation built on node variables only, which uses new constraints based on node-separators. We theoretically compare its strength to previously used MIP models in the literature and study the connected subgraph polytope associated with our new formulation. In our computational study we compare branch-and-cut implementations of the new model with two models recently proposed in the literature: one of them using the transformation into the Prize-Collecting Steiner Tree problem, and the other one working on the space of node variables only. The obtained results indicate that the new formulation outperforms the previous ones in terms of the running time and in terms of the stability with respect to variations of node weights.

Suggested Citation

  • Eduardo Álvarez-Miranda & Ivana Ljubić & Petra Mutzel, 2013. "The Maximum Weight Connected Subgraph Problem," Springer Books, in: Michael Jünger & Gerhard Reinelt (ed.), Facets of Combinatorial Optimization, edition 127, pages 245-270, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-38189-8_11
    DOI: 10.1007/978-3-642-38189-8_11
    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
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:sprchp:978-3-642-38189-8_11. 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.