A model predictive control framework for centralised management of a supply chain dynamical system

Abstract

In this paper, a centralised model predictive control (MPC) strategy is applied to control inventories in a four-echelon supply chain. The single MPC controller used in this strategy optimises globally and finds an optimal ordering policy for each node. The controller relies on a linear discrete-time state-space model to predict system outputs and the prediction can be approached by either of the two multi-step predictors depending on the measurability of the controller states. The objective function has a quadratic form and thus the resulting optimisation problem can be solved via standard quadratic programming. Simulation results show that a centralised MPC strategy is preferred because it can track customer demand and, in the meantime, maintain a proper inventory position level with reduced bullwhip effect.