Amanda J. Schmitt

Learn More
We model a retailer whose supplier is subject to complete supply disruptions. We combine discrete-event uncertainty (disruptions) and continuous sources of uncertainty (stochastic demand or supply yield), which have different impacts on optimal inventory settings. This prevents optimal solutions from being found in closed form. We develop a closed-form(More)
We demonstrate the importance of using a sufficiently long time horizon analysis when modeling inventory systems subject to supply disruptions. Several publications use single-period newsboy models to study supply disruptions, and we show that such models underestimate the risk of supply disruptions and generate sub-optimal solutions. We examine a firm with(More)
We present a model constructed for a large consumer products company to assess their vulnerability to disruption risk and quantify its impact on customer service. Risk profiles for the locations and connections in the supply chain are developed using Monte Carlo simulation, and the flow of material and network interactions are modeled using discrete-event(More)
We investigate optimal system design in a multi-location system in which supply is subject to disruptions. We examine the expected costs and cost variances of the system in both a centralized and a decentralized inventory system. We show that, when demand is deterministic and supply may be disrupted, using a decentralized inventory design reduces cost(More)
We investigate an aerospace supply chain that is subject to various types of risks in this research. Discrete-event simulation technique is used to model the flow of product and risk factors such as potential supply chain disruptions or quality issues. The underlying goal of the model is to analyze the supply chain performance under various risk scenarios(More)
  • 1