Efficient and timely response during accidents has received increased attention from practitioners and researchers. The siting of emergency service facilities (ESFs) plays a crucial role in determining the efficiency of safety protection and emergency response. This paper explores a novel multiobjective ant algorithm for the siting of ESFs. With the aid of the geographic information system, the algorithm finds a population of solutions, uses Pareto ranking to sort these solutions, and derives the Pareto front. It is demonstrated that the algorithm successfully captures a pool of nondominated solutions and thereby provides decision makers with a set of alternative solutions. The case study also demonstrates how decision makers may choose one “best” solution from the pool according to their preference or determinant criteria.
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