Model predictive control algorithm of closed-loop supply chain networks dynamic system and its bullwhip effect

A model predictive control algorithm of closed-loop supply chain networks dynamic system is studied. Based on the established system prediction model, the calculation formula of state estimation and prediction are given; the multi-stage optimal prediction model expressions are deduced; the objective function and the feedback correction method are given; the constrained optimization algorithm based on quadratic optimization is derived; and the general steps of this algorithm is given by a numerical example. The essence of this algorithm is that through the rolling optimization and continuous implementations, adjust the order quantity, production control variables, the system has good dynamic performances in the premise of stability, the bullwhip effect is restrained. In order to get the stability and coordination control method of the complex nonlinear closed-loop supply chain networks, it provides a new method.