Mohammad Miranbeigi

 A supply chain is a network of facilities and distribution entities (suppliers, manufacturers, distributors, retailers) that performs the functions of procurement of raw materials, transformation of raw materials into intermediate and finished products and distribution of finished products to customers. Between interconnected entities, there are two types of process flows: information flows, e.g., an order requesting goods, and material flows, i.e., the actual shipment of goods. The significance of the basic idea implicit in the model predictive control has been recognized a long-time ago in the operations management literature as a tractable scheme for solving stochastic multi period optimization problems, such as production planning and supply chain management, under the term receding horizon. A move suppression term that penalizes the rate of change in the transported quantities through the network increases the robustness of the control system. In this paper, we applied centralized model predictive controller and decentralized model predictive controller to both supply chain management systems dynamic models without information cycles and with it. Also we added a move suppression term to cost function that increase system robustness toward changes on demands. Through illustrative simulations, it is demonstrated that the model can accommodate supply chain networks of realistic size under deterministic and stochastic input disturbances.

  Defence date: 18/09/2010 Saturday Time: 12 am

  Where: Electronic Research Center