Optimal deployment of limited emergency response service units in a metropolitan area is of interests to public agencies. The limited emergency units not only have to respond to the demand for service by residents and businesses, but also cover Critical Infrastructures (CIs). This thesis formulates an improved optimization model to allocate different types of Emergency Response Service (ERS) units among their candidate base stations. The allocation of units must ensure maximum coverage to CIs, subject to the capacities of the base stations, service standard in terms of time to reach the CIs, and the availability of the ERS units (when there are other competing demands for services). Unlike past models, the new modeling approach accounts for the fluctuation of travel time and demand frequency at different time periods of a typical day. The applicability of the model has been demonstrated in a case study in the city of El Paso, Texas which allocates 45 fire fighting units and 23 ambulances among 34 active fire stations to cover 138 CIs, including Critical Transportation Infrastructures (CTIs), hospitals and schools.
