Consecutive robust predictive control on a supply chain network with Kalman filter state estimator

Supply chains are complicated dynamical systems triggered by customer demands. Proper selection of equipment, machinery, buildings and transportation fleets is a key component for the success of such systems. MPC has now become a standard control methodology for industrial and process systems. As supply chains can be operated sequentially, i.e., stages update their policies in series, synchronously, In this paper, locally Consecutive predictive controllers with Kalman filter estimators applied to a supply chain management system consist of one plant, two warehouses, four distribution centers and four retailers. Also a move suppression term added to cost function, that increased system robustness toward changes on demands.