Abstract Drones are projected to alter last-mile delivery, but their short travel range is a concern. This study proposes a drone delivery network design using automated battery swapping machines (ABSMs) to extend ranges. The design minimizes the long-term delivery costs, including ABSM investment, drone ownership, and cost of the delivery time, and locates ABSMs to serve a set of customers. We build a mixed-integer nonlinear program that captures the nonlinear waiting time of drones at ABSMs. To solve the problem, we create an exact solution algorithm that finds the globally optimal solution using a derivative-supported cutting-plane method. To validate the applicability of our program, we conduct a case study on the Chicago Metropolitan area using cost data from leading ABSM manufacturer and geographical data from the planning and operations language for agent-based regional integrated simulation (more commonly known as POLARIS). A sensitivity analysis identifies that ABSM service times and costs are the key parameters impacting the long-term adoption of drone delivery.

中文翻译：

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使用自动电池更换机设计无人机交付网络

摘要 无人机预计将改变最后一英里的交付方式，但其短程航程是一个问题。这项研究提出了一种无人机交付网络设计，使用自动电池交换机 (ABSM) 来扩展范围。该设计最大限度地降低了长期交付成本，包括 ABSM 投资、无人机拥有和交付时间成本，并将 ABSM 定位为服务一组客户。我们构建了一个混合整数非线性程序，用于捕获无人机在 ABSM 处的非线性等待时间。为了解决这个问题，我们创建了一个精确解算法，该算法使用导数支持的切割平面方法找到全局最优解。为了验证我们程序的适用性，我们使用领先 ABSM 制造商的成本数据和基于代理的区域综合模拟（通常称为 POLARIS）的规划和运营语言的地理数据对芝加哥大都市区进行了案例研究。敏感性分析表明，ABSM 服务时间和成本是影响无人机交付长期采用的关键参数。