IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v13y2025i7p1110-d1622305.html
   My bibliography  Save this article

Time-Dependent Multi-Center Semi-Open Heterogeneous Fleet Path Optimization and Charging Strategy

Author

Listed:
  • Tingxin Wen

    (School of Business Administration, Liaoning Technical University, Huludao 125100, China
    Ordos Research Institute, Liaoning Technical University, Ordos 017004, China)

  • Haoting Meng

    (School of Business Administration, Liaoning Technical University, Huludao 125100, China)

Abstract

To address the challenges of distribution cost and efficiency in electric vehicle (EV) logistics, this study proposes a time-dependent, multi-center, semi-open heterogeneous fleet model. The model incorporates a nonlinear power consumption measurement framework that accounts for vehicle parameters and road impedance, alongside an objective function designed to minimize the total cost, which includes fixed vehicle costs, driving costs, power consumption costs, and time window penalty costs. The self-organizing mapping network method is employed to initialize the EV routing, and an improved adaptive large neighborhood search (IALNS) algorithm is developed to solve the optimization problem. Experimental results demonstrate that the proposed algorithm significantly outperforms traditional methods in terms of solution quality and computational efficiency. Furthermore, through real-world case studies, the impacts of different distribution modes, fleet sizes, and charging strategies on key performance indicators are analyzed. These findings provide valuable insights for the optimization and management of EV distribution routes in logistics enterprises.

Suggested Citation

  • Tingxin Wen & Haoting Meng, 2025. "Time-Dependent Multi-Center Semi-Open Heterogeneous Fleet Path Optimization and Charging Strategy," Mathematics, MDPI, vol. 13(7), pages 1-27, March.
  • Handle: RePEc:gam:jmathe:v:13:y:2025:i:7:p:1110-:d:1622305
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/13/7/1110/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/13/7/1110/
    Download Restriction: no
    ---><---

    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:gam:jmathe:v:13:y:2025:i:7:p:1110-:d:1622305. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.