This research considers unmanned aerial vehicles (UAVs) that may travel at varying speeds in a last-mile delivery system involving a single truck and a fleet of UAVs. In existing truck-and-UAV delivery models that assume constant or unlimited UAV endurance, the natural conclusion is that operating UAVs at higher speeds will either decrease, or have no adverse effect on, total delivery times. However, in reality, UAV power consumption is a nonlinear function of both speed and parcel weight; flying at high speeds can dramatically reduce flight ranges, thus limiting the effectiveness of these logistics systems. This paper addresses the tradeoffs between speed and range in a new variant of the combined truck/UAV delivery problem in which UAV speeds are treated as decision variables. A three-phased algorithm is provided that dynamically adjusts UAV speeds to achieve superior performance, with the goal of minimizing the total delivery time (or makespan). Results indicate that significant time savings can be achieved by operating UAVs at variable speeds. Furthermore, under certain conditions, optimizing UAV speeds also results in shorter truck travel distances, reduced UAV energy consumption per trip, and less UAV loitering while waiting to rendezvous with the truck.

这项研究考虑了无人驾驶飞机（UAV），它可能会在最后一英里的运输系统中以单个卡车和无人驾驶飞机的速度以不同的速度行驶。在假定无人机具有恒定或无限续航能力的现有卡车和无人机交付模型中，自然得出的结论是，以更高速度运行的无人机将减少总交付时间，或者对总交付时间没有不利影响。但是，实际上，无人机的功耗是速度和包裹重量的非线性函数。高速飞行会大大减少飞行距离，从而限制了这些物流系统的有效性。本文讨论了卡车/ UAV组合交付问题的新变体中速度和航程之间的权衡，在这种变体中，将无人机速度视为决策变量。提供了一种三相算法，该算法可以动态调整无人机的速度以实现卓越的性能，以最小化总交付时间（或制造期）为目标。结果表明，通过以可变速度操作无人机可以节省大量时间。此外，在某些条件下，优化无人机速度还可以缩短卡车的行进距离，降低每次旅行的无人机能量消耗，并减少等待与卡车会合时的无人机闲置。