Ph.D. defense: Zheqi Zhang
Prioritization and Distribution of Casualties in Disaster Management
(Under the direction of Nilay Tanik Argon and Serhan Ziya)
This dissertation focused on two different problems which typically arise in the aftermath of disasters. In the first part of the dissertation, we study the problem of how casualties should be prioritized and distributed to different medical facilities in the aftermath of mass casualty incidents (MCIs) with the objective of maximizing the expected total number of survivors. Assuming that casualties have been triaged into two classes differentiated by their severity levels and medical needs, the decision-maker needs to prioritize and distribute casualties using a limited number of ambulances to multiple medical facilities with different capacities. By explicitly taking into consideration the capacity and service time at each medical facility, we formulate this sequential decision-making problem as a Markov decision process (MDP). Based on this MDP formulation, we propose heuristic policies that prescribe decisions on prioritization and distribution of casualties. We then employ discrete-event simulations to demonstrate the benefits of using the proposed heuristics against some benchmark policies under several realistic mass casualty incident scenarios such as terrorist attacks, major traffic accidents, and earthquakes.
In the second part of the dissertation, we study the resource allocation problem in urban search and rescue operations that follow natural disasters. Specifically, we consider a scenario in which some individuals are trapped at various locations within a geographical area and there is a limited time window during which these individuals can be rescued. We model the problem as an MDP. Then, we characterize the optimal policy under the assumption that individuals belong to only one of two locations. We propose heuristics for the general version of the problem. Finally, the proposed heuristics are examined with a simulation.