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

Kunpeng Wu, Shaofeng Lu (), Haoqin Chen, Minling Feng and Zenghao Lu
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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

Sustainability, 2024, vol. 16, issue 12, 1-20

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.

Keywords: drone routing problem; logistics drone; mixed-integer linear programming; adaptive large neighborhood search (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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