A Model Predictive Control framework for robust management of multi-product, multi-echelon demand networks

Model Predictive Control (MPC) is shown to provide a robust, flexible framework to stabilize inventories yet still meet customer demand with minimal safety stock. The translation of available information in the supply chain problem into MPC variables is demonstrated with a two-node supply chain example. A six-node, two-product, threeechelon demand network simulation proposed by Intel Corp. is well managed by the framework under realistic demand and information inaccuracies.