Influence of mainline schedule flexibility and volume variability on railway classification yard performance

Dick, C. Tyler

doi:10.1016/j.jrtpm.2021.100269

Cited by 6 publications

(7 citation statements)

References 35 publications

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“…Although used to model small flat switching yards (49) and hump classification yards in an abstract manner (50), Zhao and Dick (57) were the first to leverage the rail library in researching hump classification yards. Lastly, some rail companies have developed their own custom commercial yard simulations (Table 3) to specifically model certain existing hump yards (52)(53)(54)(55)(56). These models incorporate accurate track information, interactive data input, visual replay of yard movements, extensive validation, replication of scenarios considering variability, and comprehensive output metrics.…”

Section: Previous Researchmentioning

confidence: 99%

“…Lastly, some rail companies have developed their own custom commercial yard simulations (Table 3) to specifically model certain existing hump yards ( 52 – 56 ). These models incorporate accurate track information, interactive data input, visual replay of yard movements, extensive validation, replication of scenarios considering variability, and comprehensive output metrics.…”

Section: Previous Researchmentioning

confidence: 99%

“…In the most closely related work, Dick and Nishio ( 54 ) and Dick ( 55 ) examined the property of a classification yard to amplify or dampen volume variability by developing simulation experiments to study the relationship between schedule flexibility and volume variability. Although they highlighted that schedule flexibility is more detrimental to yard performance than volume variability, they suggested that future research should investigate the level of volume variation more thoroughly.…”

Section: Previous Researchmentioning

confidence: 99%

“…Previous researchers concluded that over-saturated traffic patterns (causing railcar and operational congestion) and undersaturated traffic patterns (resulting in railcars dwelling to meet minimum train sizes) both act to increase yard dwell time and the possibility of train delays (5). Besides delayed train departures, an additional complication is that the railway yard performance itself will feedback and interact with the mainline to further influence the overall railway level of service (6,7). Therefore, exploring how traffic variability affects railway performance and capacity within the network scope is crucial for railroads to improve operating strategies and provide reliable fright transportation (8).…”

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confidence: 99%

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

Zhao¹,

Dick²

2023

Transportation Research Record: Journal of the Transportation R

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

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Section: Previous Researchmentioning

confidence: 99%

Section: Previous Researchmentioning

confidence: 99%

Section: Previous Researchmentioning

confidence: 99%

mentioning

confidence: 99%

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

Zhao¹,

Dick²

2023

Transportation Research Record: Journal of the Transportation R

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“…While some studies have explicitly investigated the influence of certain factors, most have been conducted in the larger context of developing analytical, optimization and simulation approaches to classification yard performance and capacity. 24…”

Section: Previous Researchmentioning

confidence: 99%

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

Dick

2022

Proceedings of the Institution of Mechanical Engineers, Part F:

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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.

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Study of the efficiency of brake shoes

Kornienko

Olgeizer

Sukhanov

et al. 2022

Transportation Research Procedia

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Influence of mainline schedule flexibility and volume variability on railway classification yard performance

Cited by 6 publications

References 35 publications

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

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

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

Study of the efficiency of brake shoes

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