Optimizing Train Network Routing with Heterogeneous Traffic

The expected increase in long-term demand for rail traffic in North America will lead to capacity constraints. Although both infrastructure investment and operational changes can relieve congestion, careful consideration of how operational practices can affect or mitigate demand is critical for cost-effective planning for new capacity, especially when the high cost required to build and maintain infrastructure is considered. A critical aspect of capacity management is understanding the effect of heterogeneous traffic on capacity. Greater heterogeneity on a line increases interference between trains and creates more delays than would occur if all trains had similar characteristics. The present research takes into account the impact of heterogeneity and presents a new optimization framework to identify optimal train network routing. This tool will help service design managers with traffic routing and capacity utilization. The computational results show that the use of this tool can successfully reduce operational costs and provide reliable services.