Risk Management of Supply Chain Networks with Dependent Disruptions

该奖项的研究目标是建立一个框架，以研究受依赖性中断影响的供应链风险管理问题的关键问题。它开发了一个多变量马尔可夫链模型的不确定生产能力，以捕捉时间和空间的影响中断。 本文以多源和装配型两级供应链为背景，研究了供应链结构和相关干扰对供应链绩效的影响。 除了常用的两级供应链的研究工具，本研究还利用创新的方法，从几个活跃的/新的研究领域，包括多元相关理论，copula和藤蔓copula研究的定性行为和定量属性的供应链依赖中断。可供选择的包括新的供应链模型与相关的中断/随机产量，性能界限和有效的计算/模拟方法，以评估系统性能和最佳订购策略。本研究是第一个使用cupola和vine copula方法来解决供应链中的相依随机干扰问题的研究，如果成功的话，本研究的结果将导致供应链的优化设计和控制，包括随机相关的干扰。该研究的新奇在于：（1）在战略层面上，企业可以分析供应节点在不同地理位置的随机依赖性及其对需求节点的影响;（2）在运营层面上，它将帮助企业确定最优的库存策略、成本和客户服务水平。 研究工作和成果将通过出版物和网站传播。 研究生和本科生的商业和工程专业的学生将受益于课堂教学和参与研究。 将开发一个软件包，使用户能够解决相关的供应链中断问题。

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.