Risk Management of Supply Chain Networks with Dependent Disruptions

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The research objective of this award is to develop a framework to study crucial issues of risk management problems in supply chains subject to dependent disruptions. It develops a multivariate Markov chain model for uncertain production capacities to capture temporal and spatial effects of disruptions. In the context of two-echelon supply chains with either the multi-source or assembly structure, this research investigates the effect of the supply chain structure and the dependent disruptions on supply chain performance. In addition to the commonly used tools in the study of two echelon supply chains, this research also utilizes innovative methodologies from several active/new research areas, including multivariate dependence theory, copula and vine copula to study the qualitative behavior and quantitative properties of supply chains with dependent disruptions. Deliverables include new supply chain models with correlated disruptions/random yields, performance bounds and efficient computational/simulation methods to evaluate system performances and optimal ordering strategies. This research is among the first ones to address dependent stochastic disruption problems in supply chains using cupola and vine copula methods.If successful, the result of this research will lead to optimal design and control of supply chains incorporating stochastic dependence in disruptions. The novelty of the proposed research lies in: (1)at the strategic level, firms can analyze the stochastic dependence of the supply nodes operating in different geographical locations and their impact on the demand nodes, and (2) at the operational level, it will help firms in determining optimal inventory policies, costs and customer service levels. Research efforts and results will be disseminated through publications and web sites. Graduate and undergraduate business and engineering students will benefit through classroom instruction and involvement in the research. A software package enabling users to solve dependent supply chain disruption problems will be developed.