  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.
