Since ambulance providers are responsible for life-saving medical care at the scene in emergency situations and since response times are important in these situations, it is crucial that ambulances are located in such a way that good coverage is provided throughout the region. Most models that are developed to determine good base locations assume strict 0-1 coverage given a fixed base location and demand point. However, multiple applications require fractional coverage. Examples include stochastic, instead of fixed, response times and survival probabilities. Straightforward adaption of the well-studied MEXCLP to allow for coverage probabilities results in a non-linear formulation in integer variables, limiting the size of instances that can be solved by the model. In this paper, we present a linear integer programming formulation for the problem. We show that the computation time of the linear formulation is significantly shorter than that for the non-linear formulation. As a consequence, we are able to solve larger instances. Finally, we will apply the model, in the setting of stochastic response times, to the region of Amsterdam, the Netherlands.
Operations Research for Health Care

van den Berg, P. L.-J, Kommer, G.J, & Zuzáková, B. (2016). Linear formulation for the Maximum Expected Coverage Location Model with fractional coverage. Operations Research for Health Care, 8, 33–41. doi:10.1016/j.orhc.2015.08.001