IDEAS home Printed from https://ideas.repec.org/h/spr/lnopch/978-981-96-9697-0_26.html
   My bibliography  Save this book chapter

Hybrid Distribution Dispatch of Automatic Delivery Vehicles and Electric Vehicles in Front Warehouse

Author

Listed:
  • Di Zhang

    (Beijing Jiaotong University)

  • Hongjie Lan

    (Beijing Jiaotong University)

  • Chuan Wang

    (China State Shipbuilding Corporation, Limited (CSSC) 714th Research Institute)

Abstract

Amidst the expansion of fresh e-commerce, the front warehouse model has risen, praised for its prompt delivery and superior products. However, escalating operational costs have led to losses and closures across various firms, making cost reduction and efficiency crucial for sustainability. Concurrently, as unmanned logistics advances, the advantages of unmanned vehicles become evident. This paper introduces a dual-objective optimization model for unmanned and electric vehicles’ scheduling, focusing on minimizing costs and delivery times. Utilizing the NSGA-II algorithm for three customer distribution scenarios, it examines vehicle speed and compensation ratio impacts. The findings provide strategic guidance for companies at different growth stages.

Suggested Citation

  • Di Zhang & Hongjie Lan & Chuan Wang, 2025. "Hybrid Distribution Dispatch of Automatic Delivery Vehicles and Electric Vehicles in Front Warehouse," Lecture Notes in Operations Research,, Springer.
  • Handle: RePEc:spr:lnopch:978-981-96-9697-0_26
    DOI: 10.1007/978-981-96-9697-0_26
    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:978-981-96-9697-0_26. 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.