Global production networks are highly complex to manage and constantly to optimize. Recent developments such as political power changes, pandemic crises or increasing trade hurdles have significantly altered the risk exposure of global production set-ups. We use optimization and simulation tools to derive a suitable network type. We develop a global cross-shipping strategy with an integrated approach combining heuristics and simulation. We and quantify the impacts of different uncertainties, such as plant closure and high demand variation, with simula-tion, and it to compare to a local-to-local production network. Our approach makes the model easy to implement and close to real-world processes. This paper provides support for production network decision-making. We present a scientifically sound and practically feasible approach to an important actual business management problem. The developed integrated approach does not require assumptions about the production network structure or policies and is therefore applicable to a wide range of settings. In our case study, we quantify the positive impact of a global cross-shipping production network in comparison to a local-to-local approach. The result of our study helps to adjust the needed strategic and opera-tional measures to manage a global production network.