Optimal Allocation of Multiple Emergency Service Resources for Critical Transportation Infrastructure Protection

Optimal deployment of limited emergency resources in a large-scale area is of interests to public agencies at all levels. In this paper, the problem of allocating limited emergency service vehicles including fire engines, fire trucks and ambulances among a set of candidate stations is formulated as a mixed integer linear programming model, in which the objective is to maximize the service coverage to the Critical Transportation Infrastructures (CTIs). Using this model, we study the effects of demand at CTI nodes and transportation network performance on the optimal coverage to CTIs. In addition, given a fixed total budget, we are also interested in identifying the most efficient distribution of investment among the three types of emergency service vehicles. In order to cope with the uncertainty involved in some of the model parameters such as the traffic network performance, formulations based on different risk preferences are proposed. The concept of “regret” is applied to evaluate the robustness of proposed resource allocation strategies. The applicability of the proposed methodologies to high-density metropolitan area is demonstrated through a case study using data from current practice in Singapore.