Railroad companies face a difficult problem in assigning empty freight cars based on customer demand because these assignments depend on a variety of factors; these include the location of available empty cars, the urgency of the demand, and the possibilities of car substitution. In this paper, we present an optimization model implemented at Union Pacific Railroad (UP) to assign empty freight cars based on demand. The model seeks to reduce transportation costs, and improve delivery time and customer satisfaction. UP currently uses the model to make real-time assignments in a total car-management system. The model has helped UP to achieve significant reductions in its transportation costs, similar to the savings that our simulation study predicted. In addition, UP reduced the staff required for its demand fulfillment process, resulting in an ROI of 35 percent.
- Freight cars
- Linear programming