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Same-Day Delivery with Drone Resupply

Author

Listed:
  • Iman Dayarian

    (Culverhouse College of Business, University of Alabama, Tuscaloosa, Alabama 35487;)

  • Martin Savelsbergh

    (School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332;)

  • John-Paul Clarke

    (School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

Abstract

Unmanned aerial vehicles, commonly referred to as drones , have recently seen an increased level of interest as their potential use in same-day home delivery has been promoted and advocated by large retailers and courier delivery companies. We introduce a novel way to exploit drones in same-day home delivery settings: drone resupply. We consider a home delivery system in which delivery trucks are regularly resupplied by drones. Resupply can take place whenever a delivery truck is stationary and a drone can land on the truck’s roof. We introduce the vehicle routing problem with drone resupply to capture and investigate this setting. We develop different algorithms and compare their performance. Finally, we quantify the potential benefits of drone resupply and generate valuable insights for advancing this concept.

Suggested Citation

  • Iman Dayarian & Martin Savelsbergh & John-Paul Clarke, 2020. "Same-Day Delivery with Drone Resupply," Transportation Science, INFORMS, vol. 54(1), pages 229-249, January.
    • Handle: RePEc:inm:ortrsc:v:54:y:2020:i:1:p:229-249
    DOI: 10.1287/trsc.2019.0944
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    References listed on IDEAS

    as
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    2. Ozbaygin, Gizem & Ekin Karasan, Oya & Savelsbergh, Martin & Yaman, Hande, 2017. "A branch-and-price algorithm for the vehicle routing problem with roaming delivery locations," Transportation Research Part B: Methodological, Elsevier, vol. 100(C), pages 115-137.
    3. Agatz, N.A.H. & Bouman, P.C. & Schmidt, M.E., 2016. "Optimization Approaches for the Traveling Salesman Problem with Drone," ERIM Report Series Research in Management ERS-2015-011-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. Dayarian, Iman & Crainic, Teodor Gabriel & Gendreau, Michel & Rei, Walter, 2016. "An adaptive large-neighborhood search heuristic for a multi-period vehicle routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 95-123.
    5. Huang, Yixiao & Savelsbergh, Martin & Zhao, Lei, 2018. "Designing logistics systems for home delivery in densely populated urban areas," Transportation Research Part B: Methodological, Elsevier, vol. 115(C), pages 95-125.
    Full references (including those not matched with items on IDEAS)

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