关键词: 无人机与车辆协同配送, 农村电商物流, 路径优化, 两阶段算法

Abstract: Drone delivery has emerged as a significant solution to address the challenges of last-mile logistics. The collaborative delivery model between drones and vehicles overcomes the limitations of insufficient drone delivery capacity and enhances safety, making it a vital approach for drone involvement in the delivery process. To tackle the difficulties and high costs associated with “last-mile” delivery in rural e-commerce logistics, this study constructs a mixed-integer programming model. The objective is to minimize delivery costs while considering constraints such as the collaborative drone-vehicle mode and multi drone multi-parcel delivery. A two-stage algorithm is proposed to optimize the paths for drone-vehicle collaborative delivery. In the first stage, a constrained adaptive K-means algorithm is utilized to determine the range of vehicle docking points. In the second stage, an improved genetic algorithm that incorporates hill climbing and splitting operators is employed to identify the optimal delivery paths for drones and vehicles. Subsequently, a case study experiment is conducted to validate the feasibility and effectiveness of the model and algorithm. The research findings are expected to offer novel insights and valuable references for cost reduction and efficiency improvement in last-mile delivery for rural e-commerce logistics.

Key words: drone and vehicle collaborative delivery, rural logistics, path optimization, two-stage algorithm