The Multiple Ground/Aerial Parcel Delivery Problem (MGAPDP), an extension of the Ground/Aerial Parcel Delivery Problem (GAPDP), aims to find an optimal partition that minimizes the overall delivery time of all trucks by serving all destinations once and returning to the distribution center. This paper presents two heuristic solutions to the MGAPDP based on the Weighted Road Network Voronoi Diagram, i.e., Multiplicatively Weighted Road Network Voronoi Diagram (MRVD) and Additively Weighted Road Network Voronoi Diagram (ARVD). In our proposed problem, we assume that trucks travel on road networks, and UAVs move in Euclidean spaces and can be launched at any locations on roads. Each truck is equipped with a UAV, and each UAV can only be operated in Visual-Line-Of-Sight (VLOS) areas. When only one truck is considered, an intuitive approach is to check all possible locations on roads in the VLOS areas and find a globally optimal location for every destination if UAVs are used for delivery. As for multiple trucks, all of the partitions of destinations have to be considered. To avoid high computational cost for multiple truck/UAV pairs, the Weighted Road Network Voronoi Diagram is utilized to form the delivery group for each truck/UAV pair. All of the results are evaluated through extensive experiments, and the results indicate that, while both heuristic solutions effectively reduce the delivery time especially when the number of truck/UAV pairs is low, ARVD has exhibited a lower delivery time than MRVD in the majority of the considered scenarios.

多地面/空中包裹递送问题 (MGAPDP) 是地面/空中包裹递送问题 (GAPDP) 的扩展，旨在找到一个最佳分区，通过服务所有目的地一次并返回到所有卡车，从而最小化所有卡车的整体递送时间。配送中心。本文提出了两种基于加权道路网络 Voronoi 图的 MGAPDP 启发式解决方案，即乘法加权道路网络 Voronoi 图（MRVD）和加法加权道路网络 Voronoi 图（ARVD）。在我们提出的问题中，我们假设卡车在道路网络上行驶，而无人机在欧几里得空间中移动并且可以在道路上的任何位置发射。每辆卡车都配备了一架无人机，每架无人机只能在视觉视线（VLOS）区域运行。当只考虑一辆卡车时，一种直观的方法是检查 VLOS 区域道路上所有可能的位置，如果使用无人机进行交付，则为每个目的地找到一个全局最佳位置。对于多辆卡车，必须考虑目的地的所有分区。为了避免多个卡车/无人机对的高计算成本，使用加权道路网络 Voronoi 图来形成每个卡车/无人机对的交付组。所有结果都通过大量实验进行评估，结果表明，虽然两种启发式解决方案都有效地缩短了交付时间，尤其是在卡车/无人机对数量较少的情况下，但在大多数情况下，ARVD 的交付时间低于 MRVD。考虑的场景。