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Estimating flow times for containerized imports from Asia to the United States through the Western rail network

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  • Leachman, Robert C.
  • Jula, Payman

Abstract

Queuing models are introduced for estimating container dwell times at rail intermodal terminals and transit times through rail line-haul corridors. These models are statistically calibrated on industry data. The intent of these models is to estimate changes in container flow times stemming from changes in infrastructure, staffing levels at terminals, or import volumes passing through given infrastructure. Flow times estimated for individual line segments are aggregated to provide estimates of the total transit time from West Coast rail ramps to inland destination ramps for imports moving from Asia to the Continental United States in marine as well as domestic containers.

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  • Leachman, Robert C. & Jula, Payman, 2012. "Estimating flow times for containerized imports from Asia to the United States through the Western rail network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 296-309.
    • Handle: RePEc:eee:transe:v:48:y:2012:i:1:p:296-309
    DOI: 10.1016/j.tre.2011.07.002
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    Cited by:

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    3. Fan, Lei & Wilson, William W. & Dahl, Bruce, 2012. "Congestion, port expansion and spatial competition for US container imports," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(6), pages 1121-1136.
    4. Roy, Debjit & van Ommeren, Jan-Kees & de Koster, René & Gharehgozli, Amir, 2022. "Modeling landside container terminal queues: Exact analysis and approximations," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 73-102.
    5. Andreas Balster & Ole Hansen & Hanno Friedrich & André Ludwig, 2020. "An ETA Prediction Model for Intermodal Transport Networks Based on Machine Learning," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 62(5), pages 403-416, October.
    6. Disney, Stephen M. & Maltz, Arnold & Wang, Xun & Warburton, Roger D.H., 2016. "Inventory management for stochastic lead times with order crossovers," European Journal of Operational Research, Elsevier, vol. 248(2), pages 473-486.
    7. César Ducruet & Hidekazu Itoh, 2022. "Spatial Network Analysis of Container Port Operations: The Case of Ship Turnaround Times," Networks and Spatial Economics, Springer, vol. 22(4), pages 883-902, December.
    8. Li, Xinyan & Xie, Chi & Bao, Zhaoyao, 2022. "A multimodal multicommodity network equilibrium model with service capacity and bottleneck congestion for China-Europe containerized freight flows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    9. Gharehgozli, A.H. & Roy, D. & de Koster, M.B.M., 2014. "Sea Container Terminals," ERIM Report Series Research in Management ERS-2014-009-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

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