In recent years, many industries have recorded a trend of growing product variety. Thus, companies face increasing challenges to offer customers an adequate product portfolio according to their wishes. To this end, value-adding activities must be carried out on the company side, which are frequently implemented within international supply chains due to globalization. When viewing the supply and value side in an integrated fashion, the question arises to what extent an increasing product portfolio can still be produced efficiently by a supply chain. To answer this question, this thesis presents an integrated approach for planning a product portfolio and a supply chain strategy under uncertainty. The first part of the thesis proposes a domain-independent simulation approach for predicting a product portfolios market penetration. This approach considers complementary and competing offerings as well as uncertainties. The second part of the thesis covers the design problem of a supply chain strategy. To solve this problem, a stochastic optimization model is presented that considers the decision makers willingness to take risk and provides efficient supply chain strategies. Finally, in the last part of the thesis, the simulation and optimization components are combined in to a holistic set of methodological instruments to support a decision maker in terms of the integrated planning of a product portfolio and a supply chain strategy. The developed components for decision support are evaluated based on case studies.