IDEAS home Printed from https://ideas.repec.org/h/spr/oprchp/978-3-030-18500-8_3.html
   My bibliography  Save this book chapter

Integration of Drones in Last-Mile Delivery: The Vehicle Routing Problem with Drones

In: Operations Research Proceedings 2018

Author

Listed:
  • Daniel Schermer

    (Technische Universität Kaiserslautern)

Abstract

Recently, there has been a surge of interest, from both practitioners and academic researchers, that concerns the utilization of drones for civil applications. In this work, we are interested in studying the Vehicle Routing Problem with Drones (VRPD). In the VRPD, a fleet of vehicles, each of them equipped with a set of drones, is tasked with serving a given set of customers with minimal makespan. A drone may be launched from and recovered by its assigned vehicle and might move at a different velocity. However, compared to vehicles, drones possess a limited flight endurance and carrying capacity. The VRPD can be formulated as a Mixed Integer Linear Program (MILP) and, consequently, be solved by any standard MILP solver; however, only small-sized instances can be solved within a reasonable amount of time. Hence, for solving large-scale VRPD instances, we propose an algorithm based on Variable Neighborhood Search (VNS). We carried out extensive computational experiments and through our numerical results, we illustrate that drones might be beneficial with regards to a significantly reduced makespan.

Suggested Citation

  • Daniel Schermer, 2019. "Integration of Drones in Last-Mile Delivery: The Vehicle Routing Problem with Drones," Operations Research Proceedings, in: Bernard Fortz & Martine Labbé (ed.), Operations Research Proceedings 2018, pages 17-22, Springer.
    • Handle: RePEc:spr:oprchp:978-3-030-18500-8_3
    DOI: 10.1007/978-3-030-18500-8_3
    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.

    Citations

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


    Cited by:

    1. José García & José Lemus-Romani & Francisco Altimiras & Broderick Crawford & Ricardo Soto & Marcelo Becerra-Rozas & Paola Moraga & Alex Paz Becerra & Alvaro Peña Fritz & Jose-Miguel Rubio & Gino Astor, 2021. "A Binary Machine Learning Cuckoo Search Algorithm Improved by a Local Search Operator for the Set-Union Knapsack Problem," Mathematics, MDPI, vol. 9(20), pages 1-19, October.
    2. Kloster, Konstantin & Moeini, Mahdi & Vigo, Daniele & Wendt, Oliver, 2023. "The multiple traveling salesman problem in presence of drone- and robot-supported packet stations," European Journal of Operational Research, Elsevier, vol. 305(2), pages 630-643.
    3. Vicencio-Medina, Salvador J. & Rios-Solis, Yasmin A. & Ibarra-Rojas, Omar Jorge & Cid-Garcia, Nestor M. & Rios-Solis, Leonardo, 2023. "The maximal covering location problem with accessibility indicators and mobile units," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    4. Wang, Haibo & Alidaee, Bahram, 2023. "White-glove service delivery: A quantitative analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).

    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:oprchp:978-3-030-18500-8_3. 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.