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The parallel drone scheduling problem with multiple drones and vehicles

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  • Mbiadou Saleu, Raïssa G.
  • Deroussi, Laurent
  • Feillet, Dominique
  • Grangeon, Nathalie
  • Quilliot, Alain

Abstract

Delivery of goods into urban areas constitutes an important issue for logistics service providers. One of the most talked-about developments in recent years has been the potential use of unmanned aerial vehicles, or drones, for transporting packages, food, medicine, and other goods. Delivery by drones offers new possibilities, but also induces new challenging routing problems. In this paper, we address and extend the so-called Parallel Drone Scheduling Traveling Salesman Problem. Basically, in this problem, deliveries are split between a vehicle and one or several drones. The vehicle performs a classical delivery tour from the depot, while the drones are constrained to perform back and forth trips. The objective is to minimize the completion time. We extend the problem by considering several vehicles. We call it Parallel Drone Scheduling Multiple Traveling Salesman Problem. We propose a hybrid metaheuristic for its solution. The procedure starts by building a giant tour visiting all customers. Then, the giant tour is split in order to determine a set of vehicles tours (each vehicle tour following the order defined by the giant tour) and a set of customers assigned to drones. Thirdly, an improvement step move customers between vehicles or between vehicles and drones. We also propose a Mixed Integer Linear Programming formulation and a simple branch-and-cut approach. The proposed approach is validated via an experimental campaign on instances taken from the CVRPLIB11Capacited Vehicle Routing Problem LIBrary library. Computational experiments comparing several variants of the hybrid metaheuristic give some insights on this drone delivery system.

Suggested Citation

  • Mbiadou Saleu, Raïssa G. & Deroussi, Laurent & Feillet, Dominique & Grangeon, Nathalie & Quilliot, Alain, 2022. "The parallel drone scheduling problem with multiple drones and vehicles," European Journal of Operational Research, Elsevier, vol. 300(2), pages 571-589.
    • Handle: RePEc:eee:ejores:v:300:y:2022:i:2:p:571-589
    DOI: 10.1016/j.ejor.2021.08.014
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    References listed on IDEAS

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    1. Mauro Dell’Amico & Roberto Montemanni & Stefano Novellani, 2020. "Matheuristic algorithms for the parallel drone scheduling traveling salesman problem," Annals of Operations Research, Springer, vol. 289(2), pages 211-226, June.
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    4. Asma Troudi & Sid-Ali Addouche & Sofiene Dellagi & Abderrahman El Mhamedi, 2018. "Sizing of the Drone Delivery Fleet Considering Energy Autonomy," Sustainability, MDPI, vol. 10(9), pages 1-17, September.
    5. Niels Agatz & Paul Bouman & Marie Schmidt, 2018. "Optimization Approaches for the Traveling Salesman Problem with Drone," Transportation Science, INFORMS, vol. 52(4), pages 965-981, August.
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    2. Zhao, Lei & Bi, Xinhua & Li, Gendao & Dong, Zhaohui & Xiao, Ni & Zhao, Anni, 2022. "Robust traveling salesman problem with multiple drones: Parcel delivery under uncertain navigation environments," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
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    4. Zandieh, Fatemeh & Ghannadpour, Seyed Farid, 2023. "A comprehensive risk assessment view on interval type-2 fuzzy controller for a time-dependent HazMat routing problem," European Journal of Operational Research, Elsevier, vol. 305(2), pages 685-707.

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