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Impacts of Congestion and Stochastic Variables on the Network for US Container Imports

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  • Lei Fan
  • William W. Wilson

Abstract

The rapid growth of container shipments has exacerbated congestion at ports and railway corridors. The purpose of this paper is to analyse congestion in the logistics channels for container imports into the United States. A spatial stochastic optimisation model was specified which optimises ocean shipping and inland transportation networks, and accounts for congestion and risk. The model allows for risks associated with container demands, ocean shipping costs, and some of the logistical constraints. The results quantify the probability distributions of container flows under conditions of congestion and stochastic variables. The results are used to analyse inter-route and inter-port competition. © 2012 LSE and the University of Bath

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  • Lei Fan & William W. Wilson, 2012. "Impacts of Congestion and Stochastic Variables on the Network for US Container Imports," Journal of Transport Economics and Policy, University of Bath, vol. 46(3), pages 381-398, September.
    • Handle: RePEc:tpe:jtecpo:v:46:y:2012:i:3:p:381-398
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    Cited by:

    1. Di Zhang & Xinping Yan & Zaili Yang & Jin Wang, 2014. "An accident data–based approach for congestion risk assessment of inland waterways: A Yangtze River case," Journal of Risk and Reliability, , vol. 228(2), pages 176-188, April.
    2. Gillen, David & Hasheminia, Hamed, 2016. "Measuring reliability of transportation networks using snapshots of movements in the network – An analytical and empirical study," Transportation Research Part B: Methodological, Elsevier, vol. 93(PB), pages 808-824.

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