LAUSR

Origin shippers of grains and oilseeds face market price risks and costs related to handling, storage, and transporting crops. A Monte Carlo optimization model, using Material Requirement Planning (MRP), was created to minimize the mean of these costs and the 5% value‐at‐risk (VaR). The primary decision variable was the number of shuttle trains to purchase in the rail market. Additional sensitivity and stress analyses were conducted to evaluate the optimal results. Key observations include the significance of primary and secondary railcar markets for risk management, as well as the importance of managing the seasonality of farmer deliveries through forward contracting. This study also highlights the utility of subject matter expert (SME) time series modeling in Monte Carlo simulation.