A multi-objective combinatorial model of casualty processing in major incident response

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.