Supply Chain Management is a popular keyword appearing in both management science and practice regularly. Globalization and other economical developments lead to a significant increase of large and complex supply chains spanning production sites and distribution networks all over the world. Managing supply chains becomes a more and more important but also a highly challenging task. In order to improve operational or tactical decisions in this context discrete-event simulation and (mixed-integer) linear programming are popular. Both of them have advantages but also crucial drawbacks. Thus, we present a general framework to support the operational decisions for supply chain networks using a combination of an optimization model and discrete-event simulation. We show that even in case of realistic sized supply networks referring to dynamic and nonlinear aspects this new solution method is able to cope with the given complexity and finds solutions with reasonable computational effort.

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