In this paper, we consider an Emergency Medical Services (EMS) system with two types of medical response units: Rapid Responder Ambulances (RRAs) and Regular Transport Ambulances (RTAs). The key difference between both is that RRAs are faster, but they lack the ability to transport a patient to the hospital. To maintain the ability to respond to emergency requests timely when ambulances get busy, we consider compliance tables, which indicate the desired locations of the available ambulances. Our system brings forth additional complexity to the problem of computing optimal compliance tables, as we have two kinds of ambulances. We propose an Integer Linear Program (ILP) computing compliance tables for such a system, which uses outcomes of a Hypercube model as input parameters. Moreover, we include nestedness constraints and we set bounds on the relocation times in the ILP. To obtain more credible results, we simulate the computed compliance tables for different input parameters. Results show that bounding the time a relocation may last is beneficial in certain settings. Besides, including the nestedness constraints ensures that the number of relocations and the relocation time is reduced, while the performance stays unaffected.