论文标题
沟通意识到的无人机交付问题
Communication-aware Drone Delivery Problem
论文作者
论文摘要
已经引入了无人机交付问题（DDP），以在最后一英里的交付操作中包括飞机，以提高效率。但是，现有研究并未纳入此类交付操作的通信质量要求。这项研究介绍了通信感知的DDP（C-DDP），其中包含移交和中断约束。特别是，无人机的任何旅行来交付客户包都必须需要小于一定数量的切换操作，并且不能超过预定义的中断持续时间阈值。作者开发了混合整数编程（MIP）模型，以最大程度地降低航班距离，同时满足沟通约束以及客户的时间窗口。我们提出了一种遗传算法（GA），该算法可以解决大型实例，并将其性能与现成的MIP求解器进行比较。计算结果表明，GA可以胜过MIP求解器来解决较大实例，这是一个更好的选择。
The drone delivery problem (DDP) has been introduced to include aerial vehicles in last-mile delivery operations to increase efficiency. However, the existing studies have not incorporated the communication quality requirements of such a delivery operation. This study introduces the Communication-aware DDP (C-DDP), which incorporates handover and outage constraints. In particular, any trip of a drone to deliver a customer package must require less than a certain number of handover operations and cannot exceed a predefined outage duration threshold. The authors develop a Mixed Integer Programming (MIP) model to minimize the total flight distance while satisfying communication constraints as well as the time windows of customers. We present a Genetic Algorithm (GA) that can solve large instances, and compare its performance with an off-the-shelf MIP solver. Computational results show that the GA can outperform the MIP solver for solving larger instances and is a better option.
