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The efficient response to a disaster plays an important role in decreasing its impact on affected victims. In some cases, the high volume of potential casualties and the urgency of a fast response increase the complexity of the disaster response mission. Such cases have created the need for an effective and efficient emergency logistics response. This paper identifies three research gaps in emergency logistics and develops a framework to fill these gaps. The framework includes a multi-objective (MO) optimization model and a heuristic algorithm that can obtain nearly optimal emergency medical response strategies characterized by the selection of the following: (1) locations of temporary emergency units (TEUs), (2) dispatching strategies of emergency vehicles to evacuate injured victims to the TEUs, and (3) number of victims to evacuate to each unit. The objectives of the optimization model are to minimize the response time and cost of the response strategy. An evolutionary algorithm is developed to solve the model and find an approximate set of Pareto optimal solutions where each solution represents a different emergency medical response strategy. This approach can help decision-makers to evaluate the tradeoffs among different strategies. Three experiments are presented to exemplify the model. |
