| Supply chain risk management is a recent emerging area which has caused many researchers interest since it has significant effects on the performance of the whole supply chain. In this dissertation, supply chain risk is defined as two categories: inherent risk and disruption risk. Inherent risk refers to organizational intrinsic uncertainty, such as uncertain demand, uncertain price, and so on. Disruption risk refers to natural disruption or man-made disruption, such as earthquake and emergency events. Most research focuses on inherent risk, but very few quantitative models have been studied for disruption risk. The objectives are to develop a quantitative model to evaluate the combined effects of inherent risk and disruption risk on the performance of the whole supply chain, devise optimal policies to mitigate the effect of disruption, and provide robust strategies to manage the supply chain risks.;The jump-diffusion model is used to model the supply chain risk, which includes both inherent and disruption risks. Mathematical stochastic control theory is applied to this model in order to find out the optimal control policies. A general verification theory is derived to find the optimal control policies, and this theory lays a theoretic foundation for our research topics. There are five research topics investigated in this dissertation, including optimal transportation dispatching under demand disruption, optimal purchasing time under raw material price disruption, supply chain risk analysis under demand disruption, production control and supplier selection under demand disruption, and a framework of the combined stochastic control applied in supply chain risk. These topics range from theoretical modeling to practical solution techniques. Our approach provides a framework to investigate supply chain risk and quantitative analysis for tactical and operational management. |
