Model predictive control strategy for petrochemical supply chain planning under uncertainty

This paper applies model predictive control (MPC), which is an advanced control technique to supply chain planning arising in petrochemical industry. A multi-period, multi-product planning under uncertainty is discussed. The usefulness of MPC as a tactical decision policy is integrated to the model. Based on the discrete-time modeling method, a mixed integer linear programming (MILP) model is introduced, in which the nonlinear part is converted to linear problem using fuzzy possibility method. The effectiveness of the proposed model is illustrated through a refinery case.