IDEAS home Printed from https://ideas.repec.org/p/sek/iacpro/0201371.html
   My bibliography  Save this paper

Two-Phase Heuristic For Capacitated Degree Constrained Min-Sum Arborescence

Author

Listed:
  • Rakesh Kawatra

    (Minnesota State University-Mankato)

Abstract

We present a two-phase heuristic for designing a capacitated degree constrained min sum arborescence. For a given directed graph G(V,E) where V={0, 1,?,n} with nonnegative costs Cij for each (i,j) ? E, our heuristic finds a minimum cost arborescence rooted at node 1 that spans the set {0, 1,?,n} with a constraint that the number of edges incident on each node i ? {1,2,?,n} is limited to a predetermined number constrained by the number of ports available on them (degree constraint). Additionally, the polling and response time constraints limit the number of nodes in the sub-trees rooted at node 1 (capacity constraint) predefined number. Lower bounds given for the integer programming formulation of the problem by our heuristic is used to estimate the quality of the solutions. Experimental results over a wide range of problem structures show that the two-phase heuristic gives verifiably good solutions to this problem.

Suggested Citation

  • Rakesh Kawatra, 2014. "Two-Phase Heuristic For Capacitated Degree Constrained Min-Sum Arborescence," Proceedings of International Academic Conferences 0201371, International Institute of Social and Economic Sciences.
    • Handle: RePEc:sek:iacpro:0201371
    as

    Download full text from publisher

    File URL: https://iises.net/proceedings/10th-international-academic-conference-vienna/table-of-content/detail?cid=2&iid=53&rid=1371
    File Function: First version, 2014
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Integer programming; network design; heuristics; Lagrangian relaxation;
    All these keywords.

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

    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:sek:iacpro:0201371. 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: Klara Cermakova (email available below). General contact details of provider: https://iises.net/ .

    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.