Influence of traffic complexity on railway gravity hump classification yard performance and capacity

Abstract

An optimal freight train plan requires practitioners to find a balance between mainline and yard efficiencies by adjusting the complexity of the yard operation and evaluating trade-offs between the throughput volume, number of blocks and number of trains handled at a given classification (marshalling) yard. To increase knowledge of these trade-offs, YardSYM is used to model the Belt Railway Company of Chicago (BRC) Clearing Yard, a major gravity hump classification yard that processes approximately 3000 railcars per day. The experimental design specifies traffic patterns of varying complexity designed to determine the fundamental relationship between yard throughput volume, the total number of blocks assembled in the yard, and the level of service. Simulation results indicate that yard performance decreases as railcar volume increases and as the number of blocks increases. The simulation results also demonstrate the challenge of two diametrically opposed objectives for yard operators: maximizing railcar connections to outbound trains while departing outbound trains on schedule. Improved knowledge of these relationships can be implemented to advance network, traffic assignment, and blocking models, and allow practitioners to make more informed hump yard operating decisions that improve the efficiency of carload traffic and manifest train operations.