A Cooperative Distributed Model Predictive Control Approach to Supply Chain Management

Effective supply chain management is a crucial competency for modern enterprises, but the issue has not been systemically addressed. To this end, we develop a distributed model predictive control (DMPC) approach with minimal information exchange and communication to handle supply chain operations and management. Therein, each decision maker relies on an agent with local information and they are collaborating to minimize a global cost function that measures the control performance of the entire network. The information flow topology is utilized to sequentially solve the DMPC optimization problem. The control sequence of downstream nodes is predicted with information transmitted to the upstream nodes. The stability of the proposed DMPC scheme is provably guaranteed. Finally, a numerical example is presented to verify the effectiveness of the proposed scheme.