This paper deals with the problem of locating emergency vehicles in an urban area. We formulate an optimization model that extends previous work by allowing stochastic travel times, unequal vehicle utilizations, various call types, and service times that depend on call location. The basis of the model is a procedure for approximating the performance of spatially distributed queueing systems. In previous work the model has been validated using data from the Tucson Emergency Medical Services (EMS). We test the computational effectiveness of pairwise interchange heuristics on 192 test problems. Demand and service time components of the test data are generated using characteristics of the Tucson data set. For these test problems, simple pairwise interchange techniques yield reasonable solutions with little computational effort. Also, solutions obtained from the model differ from those generated using methods previously presented in the literature.
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