The Mixed Integer Linear Programming (MILP) technique is a useful tool for the optimization of energy systems. However, the introduction of integers in linear models results in a severe drawback because the ranging process is no longer available. Therefore, it is not possible to study what happens to the solution if input data are changed. In this paper, we compare a MILP model of a building with a simulation model of an identical case. Both models describe a building with a number of possible retrofits. Using the MILP technique, the optimal retrofit strategy is calculated, after which certain input data are changed. The optimization results in the lowest possible Life-Cycle Cost (LCC) of the building, and the paper describes how much the LCC will change if the property owner chooses other solutions. An increase in a particular data value may cause the LCC to increase or decrease. It may also be unchanged. Only a few data reduce the LCC when their values are increased.