The Salzgitter Flachstahl GmbH plans a shift in their production program, which might require adaptions in the logistics. A discrete event simulation model is used to evaluate the impact of the new production program on logistics and the effects of various adaptations. In practice, however, optimization algorithms are applied in this system to facilitate resource planning, e.g., for loading train wagons or crane scheduling. To develop a valid production system model, it was necessary to implement optimization algorithms directly within the simulation and execute them iteratively during the simulation run. Using this approach, different adaptions of the logistic system could be evaluated. The approach to implementing iterative optimization-based simulation in practice and the lessons learned are reported.