Quantifying the Relative Influence of Railway Hump Classification Yard Performance Factors

Abstract

Single-railcar freight shipments that move in multiple freight trains and are sorted at several classification yards between origin and destination remain an important source of traffic and revenue for North American railways. Despite the role of both mainlines and yards in freight rail transportation performance, little attention is devoted to investigations of classification yard performance, and few yard capacity models and tools are available. To address this need, this paper seeks to quantify the relative influence of different factors on several yard performance metrics. Simulation experiments conducted with YardSYM, a discrete-event simulation model developed specifically to analyze hump classification yards, examine varying the volume, number of blocks, block size distribution, number of outbound trains, train departure distribution, train arrival time variability, and arriving block volume variability. In addition to the expected sensitivity of yard performance to railcar throughput volume, the most influential factors change depending on the particular yard performance metric, emphasizing the criticality of matching performance metrics to railroad business objectives. The results of this research serve to screen variables for the future development of multivariable yard performance models and facilitate more informed business decisions regarding yard operating plans that make more efficient and economical use of existing yard capacity.