Process simulation has many applications that are closely related to optimization. Finding optimal steering parameters for the simulated processes is an activity in which the simulation model is often used as an evaluation function to an optimization procedure. Combining optimization and simulation has been achieved in the past already, however optimization procedures implemented in simulation software are often only black box solvers that are difficult to change, extend or parameterize. Optimization software frameworks on the other hand host a range of suitable algorithms, but often lack the ability to describe and run simulation models. Exchange protocols have been proposed in the past, however the interchange has still proven to be complex and work on simplification is ongoing. In this work, we want to pursue a different approach. We intend to integrate simulation capabilities into an optimization framework and thus want to better support applications for simulation-based optimization. We will describe a suitable generic simulation framework and its integration into HeuristicLab. A case study is presented as a demonstration of its usefulness.