IDEAS home Printed from https://ideas.repec.org/a/spr/aqjoor/v21y2023i4d10.1007_s10288-022-00527-z.html
   My bibliography  Save this article

An efficient branch-and-cut algorithm for the parallel drone scheduling traveling salesman problem

Author

Listed:
  • Minh Anh Nguyen

    (Phenikaa University)

  • Hai Long Luong

    (Phenikaa University)

  • Minh Hoàng Hà

    (Phenikaa University)

  • Ha-Bang Ban

    (Hanoi University of Science and Technology)

Abstract

This paper proposes an efficient branch-and-cut algorithm to exactly solve the parallel drone scheduling traveling salesman problem. The problem is first formulated as a mixed integer linear program with truck-flow variables defined on undirected edges, not on directed arcs as in existing models. The formulation is then strengthened by valid inequalities and the branch-and-cut algorithm is developed. The experimental results show that our algorithm can find optimal solutions for all existing instances, but two in a reasonable running time. To make the problem more challenging for future solution methods, we introduce two new sets of 120 larger instances with the number of customers varying from 318 to 783 and test our algorithm and investigate the performance of state-of-the-art metaheuristics on these instances. We show that the proposed algorithm can steadily solve the instances with up to 400 customers to optimality. Optimal solutions of several cases with 600 and 783 customers are also found by our algorithm. This is the first time problems of such a large size are optimally solved.

Suggested Citation

  • Minh Anh Nguyen & Hai Long Luong & Minh Hoàng Hà & Ha-Bang Ban, 2023. "An efficient branch-and-cut algorithm for the parallel drone scheduling traveling salesman problem," 4OR, Springer, vol. 21(4), pages 609-637, December.
    • Handle: RePEc:spr:aqjoor:v:21:y:2023:i:4:d:10.1007_s10288-022-00527-z
    DOI: 10.1007/s10288-022-00527-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10288-022-00527-z
    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/s10288-022-00527-z?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.

    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:aqjoor:v:21:y:2023:i:4:d:10.1007_s10288-022-00527-z. 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.