Quantifying the Influence of Volume Variability on Railway Hump Classification Yard Performance with AnyLogic Simulation

On North American freight railways, railcars transported in manifest (carload) trains are required to stop and be resorted at multiple intermediate classification (marshalling) yards before reaching their destination. Yard dwell time comprises the majority of total railcar transit time, railway yard congestion can further promote mainline train delay. However, most literature on railroad performance has focused mainline, few previous studies specifically examined impacts vast volume fluctuation because variable shipping demand. To understand behavior under these conditions, this paper explores influence inbound traffic variability outbound size using a novel AnyLogic simulation model. A series experiments quantify interaction between as measured by different metrics overall volumes blocking patterns. The results impact variation level service, suggest that forming longer blocks leads shorter times but larger sensitivity compared short blocks. Comparison arrival departure distributions indicates moderate fluctuations while causing delays. These serve quantitative foundation for study recovery patterns following surges resulting interactions mainlines network, inform operating plan adjustments better manage utilize existing resources.