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An Energy-Efficient Logistic Drone Routing Method Considering Dynamic Drone Speed and Payload

Author

Listed:
  • Kunpeng Wu

    (Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou 511442, China)

  • Shaofeng Lu

    (Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou 511442, China)

  • Haoqin Chen

    (Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou 511442, China)

  • Minling Feng

    (Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou 511442, China)

  • Zenghao Lu

    (Fujian Zhongli Technology Co., Quanzhou 362100, China)

Abstract

Unmanned aerial vehicles (UAVs), or drones, are recognized for their potential to improve efficiency in last-mile delivery. Unlike the vehicle routing problem, drone route design is challenging due to several operational signatures, such as speed optimization, multi-trip operation, and energy consumption estimation. Drone energy consumption is a nonlinear function of both speed and payload. Moreover, the high speed of drones can significantly curtail the drone range, thereby limiting the efficiency of drone delivery systems. This paper addresses the trade-off between speed and flight range in a multi-trip drone routing problem with variable flight speeds (DRP–VFS). We propose a new model to specifically consider energy constraints using a nonlinear energy consumption model and treat drone speeds as decision variables. The DRP–VFS is initially formulated using mixed-integer linear programming (MILP) to minimize energy consumption. To solve large-scale instances, we propose a three-phase adaptive large neighborhood search (ALNS) algorithm and compare its performance with a commercial MIP solver. The experimental results demonstrate that the proposed method is capable of effectively identifying suboptimal solutions in practical scenarios. Furthermore, results indicate that operating drones at variable speeds leads to about 21% energy savings compared to fixed speeds, with advantages in cost savings and range extension.

Suggested Citation

  • Kunpeng Wu & Shaofeng Lu & Haoqin Chen & Minling Feng & Zenghao Lu, 2024. "An Energy-Efficient Logistic Drone Routing Method Considering Dynamic Drone Speed and Payload," Sustainability, MDPI, vol. 16(12), pages 1-20, June.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:12:p:4995-:d:1413029
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    References listed on IDEAS

    as
    1. 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.
    2. Cheng, Chun & Adulyasak, Yossiri & Rousseau, Louis-Martin, 2020. "Drone routing with energy function: Formulation and exact algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 364-387.
    3. Wang, Zheng & Sheu, Jiuh-Biing, 2019. "Vehicle routing problem with drones," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 350-364.
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