AI 中文总结
研究基于分层轮辐式无人机网络交付时间敏感医疗物品，提出混合整数规划模型，定制精确解法和启发式算法，通过实际案例和测试数据验证，其解法比Gurobi求解器快，多程交付更具成本效益。
AI 中文摘要
及时在区域医疗网络中分发医疗物品（如全血和疫苗），传统地面交付系统存在响应受限和运营低效问题。利用基于无人机的交付系统是有前景的解决方案。本文研究分层轮辐式无人机网络，考虑不同特性无人机和多程交付模式，提出混合整数规划模型及定制精确解法、启发式算法。基于实际案例和飞行测试数据表明，精确和启发式解法比Gurobi求解器分别快31倍和3375倍，多程交付比单程更具成本效益。
英文摘要
Timely distribution of medical items (e.g., whole blood and vaccines) across regional healthcare networks often requires high-volume delivery operations from central facilities (e.g., blood banks) to intermediate regional hospitals, followed by rapid last-mile deliveries to points of injury. Traditional ground-based delivery systems often suffer from limited responsiveness (e.g., traffic congestion) and operational inefficiencies (e.g., blood waste). Leveraging aerial-drone-based delivery systems offers a promising solution for the fast and efficient delivery of time-sensitive medical items across regional healthcare networks. Therefore, we study a hierarchical hub-and-spoke drone-based network for delivering time-sensitive medical items with distinct release and due times to fixed and mobile delivery destinations. We consider a heterogeneous fleet of drones with distinct characteristics (e.g., cost, battery capacity, and speed) and different multi-trip delivery modes. We propose an efficient mixed-integer programming model for location/allocation of mobile delivery destinations, as well as routing and scheduling drones to minimize the total investment and operational costs of the drone delivery network while maintaining the delivery due times. We develop a customized exact solution method integrating problem-specific reformulations and dynamic cutting planes, as well as a fast heuristic algorithm by leveraging a simplified problem variant. Results based on a real-life case study of whole blood delivery data from Pendleton, Oregon, United States, and actual drone flight test data demonstrate that our exact and heuristic solution methods are 31 and 3,375 times faster, respectively, than the Gurobi solver. Results also show that allowing drones to perform multiple trips is 142.8% more cost-efficient than single trips.
