IDEAS home Printed from https://ideas.repec.org/h/spr/spochp/978-3-031-58919-5_8.html
   My bibliography  Save this book chapter

A Simulated Annealing Heuristic Approach for the Energy Minimizing Electric Vehicle Routing Problem with Drones

In: Disruptive Technologies and Optimization Towards Industry 4.0 Logistics

Author

Listed:
  • Nikolaos A. Kyriakakis

    (Technical University of Crete)

  • Themistoklis Stamadianos

    (Technical University of Crete)

  • Magdalene Marinaki

    (Technical University of Crete)

  • Yannis Marinakis

    (Technical University of Crete)

Abstract

The Electric Vehicle Routing Problem with Drones (EVRPD) is a recently proposed VRP that combines two state-of-the-art means of transportation, electric ground vehicles (EVs) and drones, intending to minimize total energy consumption. The payload weight is considered the element that has the greatest impact on the energy consumption rate. The EVRPD assumes packages of different weight classes. The EVs serve as mobile depots, from which drones are deployed to deliver the packages. Both vehicle types have quantity, weight, and energy limitations. The Simulated Annealing heuristic of this research follows a population-based approach, which utilizes neighborhood operators to evolve the solutions. Three different temperature decaying strategies are tested on the EVRPD benchmark instances found in the literature, and their computational results are compared and discussed.

Suggested Citation

  • Nikolaos A. Kyriakakis & Themistoklis Stamadianos & Magdalene Marinaki & Yannis Marinakis, 2024. "A Simulated Annealing Heuristic Approach for the Energy Minimizing Electric Vehicle Routing Problem with Drones," Springer Optimization and Its Applications, in: Athanasia Karakitsiou & Athanasios Migdalas & Panos M. Pardalos (ed.), Disruptive Technologies and Optimization Towards Industry 4.0 Logistics, pages 227-246, Springer.
    • Handle: RePEc:spr:spochp:978-3-031-58919-5_8
    DOI: 10.1007/978-3-031-58919-5_8
    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 search for a similarly titled item that would be available.

    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:spochp:978-3-031-58919-5_8. 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.