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Cooperative route planning for the drone and truck in delivery services: A bi-objective optimisation approach

Author

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  • Kangzhou Wang
  • Biao Yuan
  • Mengting Zhao
  • Yuwei Lu

Abstract

The deployment of drones to support the last-mile delivery has been initially attempted by several companies such as Amazon and Alibaba. The complementary capabilities of the drone and the truck pose an innovative delivery mode. The relevant optimisation problem associated with this new mode, known as the travelling salesman problem with drone (TSP-D), aims to find the coordinated routes of a drone and a truck to serve a list of customers. In practice, managers sometimes intend to attain a compromise between operational cost and completion time. Therefore, this article addresses a bi-objective TSP-D considering both objectives. An improved non-dominated sorting genetic algorithm (INSGA-II) is proposed to solve the problem. Specifically, the label algorithm-based decoding method, the fast non-dominated sorting approach, the crowding-distance computation procedure, and the local search component are devised to accommodate the features of the problem. Furthermore, the first Pareto front obtained by the INSGA-II is improved by a post-optimisation component. Computational results validate the competitive performance of the proposed algorithm. Meanwhile, the trade-off analysis demonstrates the relationship between operational cost and completion time and provides managerial insights for managers designing reasonable compromise routes.

Suggested Citation

  • Kangzhou Wang & Biao Yuan & Mengting Zhao & Yuwei Lu, 2020. "Cooperative route planning for the drone and truck in delivery services: A bi-objective optimisation approach," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(10), pages 1657-1674, October.
  • Handle: RePEc:taf:tjorxx:v:71:y:2020:i:10:p:1657-1674
    DOI: 10.1080/01605682.2019.1621671
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    Cited by:

    1. Jianxun Li & Hao Liu & Kin Keung Lai & Bhagwat Ram, 2022. "Vehicle and UAV Collaborative Delivery Path Optimization Model," Mathematics, MDPI, vol. 10(20), pages 1-22, October.
    2. Jiang, Jie & Dai, Ying & Yang, Fei & Ma, Zujun, 2024. "A multi-visit flexible-docking vehicle routing problem with drones for simultaneous pickup and delivery services," European Journal of Operational Research, Elsevier, vol. 312(1), pages 125-137.
    3. Yin, Yunqiang & Li, Dongwei & Wang, Dujuan & Ignatius, Joshua & Cheng, T.C.E. & Wang, Sutong, 2023. "A branch-and-price-and-cut algorithm for the truck-based drone delivery routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1125-1144.
    4. 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).
    5. Yin, Yunqiang & Yang, Yongjian & Yu, Yugang & Wang, Dujuan & Cheng, T.C.E., 2023. "Robust vehicle routing with drones under uncertain demands and truck travel times in humanitarian logistics," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).

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