IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v60y2022i17p5332-5353.html
   My bibliography  Save this article

Branch-and-price-and-cut methods for the electric vehicle routing problem with time windows

Author

Listed:
  • Ece Naz Duman
  • Duygu Taş
  • Bülent Çatay

Abstract

In this paper, we address the electric vehicle routing problem with time windows and propose two branch-and-price-and-cut methods based on a column generation algorithm. One is an exact algorithm whereas the other is a heuristic method. The pricing sub-problem of the column generation method is solved using a label correcting algorithm. The algorithms are strengthened with the state-of-the-art acceleration techniques and a set of valid inequalities. The acceleration techniques include: (i) an intermediate column pool to prevent solving the pricing sub-problem at each iteration, (ii) a label correcting method employing the ng-route algorithm adopted to our problem, (iii) a bidirectional search mechanism in which both forward and backward labels are created, (iv) a procedure for dynamically eliminating arcs that connect customers to remote stations from the network during the path generation, (v) a bounding procedure providing early elimination of sub-optimal routes, and (vi) an integer programming model that generates upper bounds. Numerical experiments are conducted using a benchmark data set to compare the performances of the algorithms. The results favour the heuristic algorithm in terms of both the computational time and the number of instances solved. Moreover, the heuristic algorithm is shown to be specifically effective for larger instances. Both algorithms introduce a number of new solutions to the literature.

Suggested Citation

  • Ece Naz Duman & Duygu Taş & Bülent Çatay, 2022. "Branch-and-price-and-cut methods for the electric vehicle routing problem with time windows," International Journal of Production Research, Taylor & Francis Journals, vol. 60(17), pages 5332-5353, September.
  • Handle: RePEc:taf:tprsxx:v:60:y:2022:i:17:p:5332-5353
    DOI: 10.1080/00207543.2021.1955995
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2021.1955995
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207543.2021.1955995?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wang, Ruiting & Keyantuo, Patrick & Zeng, Teng & Sandoval, Jairo & Vishwanath, Aashrith & Borhan, Hoseinali & Moura, Scott, 2024. "Robust routing for a mixed fleet of heavy-duty trucks with pickup and delivery under energy consumption uncertainty," Applied Energy, Elsevier, vol. 368(C).
    2. Seyfi, Majid & Alinaghian, Mahdi & Ghorbani, Erfan & Çatay, Bülent & Saeid Sabbagh, Mohammad, 2022. "Multi-mode hybrid electric vehicle routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).

    More about this item

    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:taf:tprsxx:v:60:y:2022:i:17:p:5332-5353. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    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.