During the emergency response to mass casualty incidents decisions relating to the extrication, treatment and transporting of casualties are made in a real-time, sequential manner. In this paper we describe a novel combinatorial optimization model of this problem which acknowledges its temporal nature by employing a scheduling approach. The model is of a multi-objective nature, utilizing a lexicographic view to combine objectives in a manner which capitalizes on their natural ordering of priority. The model includes pertinent details regarding the stochastic nature of casualty health, the spatial nature of multi-site emergencies and the dynamic capacity of hospitals. A Variable Neighborhood Descent metaheuristic is employed in order to solve the model. The model is evaluated over a range of potential problems, with results confirming its effective and robust nature. 
A multi-objective combinatorial model of casualty processing in major incident response