This study entails the development of a planning model utilizing Centralized Model Predictive Control (CMPC) to optimize the flow of physical goods throughout a network of supply chain nodes, utilizing a Mixed-Integer Linear Programming (MILP) approach to determine the optimal decision variables. Specifically, a Current State CMPC model was created to reflect the current outbound logistic network at Heineken Zoeterwoude, where information asymmetries are known to impact the accuracy of the outbound logistic planning tool. The Current State model was compared against a Future State model, where real-time data is available, thereby eliminating the aforementioned information asymmetries. By assessing four key performance indicators, it was found that the Future State model enables considerably better performance of the logistic network, even during peak production.