论文标题
设施位置，具有拥堵和优先级的紧急交付
Facility Location with Congestion and Priority in Drone-Based Emergency Delivery
论文作者
论文摘要
由于他们的快速交付，交通限制减少以及人力需求较低，因此在紧急情况下，无人机越来越多地部署，以交付药物，血液和考试套件，例如药物，血液和考试套件。本文考虑了在紧急交付中使用无人机作为移动服务器的设施位置模型。该模型共同优化了设施的位置，在开放设施中部署的无人机的容量以及需求的分配，目的是在所有需求站点之间进行公平的响应时间。为此，我们采用队列对无人机请求的系统充血进行建模，并考虑三个排队学科：非优先级，静态优先级和动态优先级。对于每个学科，我们将模型近似为混合二阶圆锥程序（MISOCP），可以在商业求解器中轻松解决。我们进行了广泛的计算实验，以证明方法的有效性和准确性。此外，我们比较了三个排队学科和各种问题参数下的系统性能，从中我们向紧急交付中的决策者提出了运营建议。
Thanks to their fast delivery, reduced traffic restrictions, and low manpower need, drones have been increasingly deployed to deliver time-critical materials, such as medication, blood, and exam kits, in emergency situations. This paper considers a facility location model of using drones as mobile servers in emergency delivery. The model jointly optimizes the location of facilities, the capacity of drones deployed at opened facilities, and the allocation of demands, with an objective of equitable response times among all demand sites. To this end, we employ queues to model the system congestion of drone requests and consider three queuing disciplines: non-priority, static priority, and dynamic priority. For each discipline, we approximate the model as a mixed-integer second-order conic program (MISOCP), which can readily be solved in commercial solvers. We conduct extensive computational experiments to demonstrate the effectiveness and accuracy of our approach. Additionally, we compare the system performance under the three queuing disciplines and various problem parameters, from which we produce operational recommendations to decision makers in emergency delivery.
