IDEAS home Printed from https://ideas.repec.org/a/ids/ijpman/v11y2018i4p399-419.html
   My bibliography  Save this article

A cluster first-route second approach for a capacitated vehicle routing problem: a case study

Author

Listed:
  • Serap Ercan Comert
  • Harun Resit Yazgan
  • Sena Kır
  • Furkan Yener

Abstract

In this study, a capacitated vehicle routing problem (CVRP) which dealt with minimum distance routes for vehicles that serve customers having specific demands from a common warehouse under a capacity constraint. This problem is NP hard. We solved the problem in a hierarchical way (i.e., cluster-first route-second method). Firstly, customers were clustered using three different clustering algorithms; K-means, K-medoids and random clustering with considering a vehicle capacity. Secondly, routing problems for each cluster were solved using a branch and bound algorithm. The proposed solution strategy was employed on a case study in a supermarket chain. Results of numerical investigation were presented to illustrate the effectiveness of the algorithms using paired sample t tests. The results illustrated that the K-medoids algorithm provided better solution than the others.

Suggested Citation

  • Serap Ercan Comert & Harun Resit Yazgan & Sena Kır & Furkan Yener, 2018. "A cluster first-route second approach for a capacitated vehicle routing problem: a case study," International Journal of Procurement Management, Inderscience Enterprises Ltd, vol. 11(4), pages 399-419.
    • Handle: RePEc:ids:ijpman:v:11:y:2018:i:4:p:399-419
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=92766
    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. Sean Grogan & Robert Pellerin & Michel Gamache, 2021. "Using tornado-related weather data to route unmanned aerial vehicles to locate damage and victims," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(4), pages 905-939, December.
    2. Ouyang, Zhiyuan & Leung, Eric K.H. & Huang, George Q., 2023. "Community logistics and dynamic community partitioning: A new approach for solving e-commerce last mile delivery," European Journal of Operational Research, Elsevier, vol. 307(1), pages 140-156.

    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:ijpman:v:11:y:2018:i:4:p:399-419. 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=255 .

    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.