IDEAS home Printed from https://ideas.repec.org/h/spr/lnopch/978-3-032-14489-8_12.html

A Combinatorial Algorithm for the Platoon Formation Problem for Electric Commercial Vehicles

In: Proceedings of the International Conference on Industrial Logistics (ICIL) 2025

Author

Listed:
  • Muhammad Ridwan Reza Nugraha

    (Khalifa University, Department of Mathematics and Research Center on Digital Supply Chain and Operations Management)

  • Mouna Kchaou-Boujelben

    (UAE University, College of Business and Economics and Emirates Center for Mobility Research)

  • Young-Ji Byon

    (Northwestern College, Department of Engineering)

  • Adriana F. Gabor

    (Khalifa University, Department of Mathematics and Research Center on Digital Supply Chain and Operations Management)

Abstract

This paper focuses on the platoon formation planning problem for electric commercial vehicles, considering charging constraints. We present a polynomial time heuristic designed to efficiently handle large scale instances. To evaluate its performance, we compare the heuristic with a Mixed Integer Linear Programming (MILP) model in terms of solution quality and computational time. Results show that the heuristic achieves near-optimal solutions for small and medium sized instances and can solve problems involving up to 2,000 vehicles in less than 7 s, while the MILP requires over an hour to solve instances with more than 100 vehicles.

Suggested Citation

  • Muhammad Ridwan Reza Nugraha & Mouna Kchaou-Boujelben & Young-Ji Byon & Adriana F. Gabor, 2026. "A Combinatorial Algorithm for the Platoon Formation Problem for Electric Commercial Vehicles," Lecture Notes in Operations Research, in: U. Aytun Ozturk & Petri T. Helo (ed.), Proceedings of the International Conference on Industrial Logistics (ICIL) 2025, pages 113-121, Springer.
  • Handle: RePEc:spr:lnopch:978-3-032-14489-8_12
    DOI: 10.1007/978-3-032-14489-8_12
    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:lnopch:978-3-032-14489-8_12. 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.