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Reliable Routing of Road-Rail Intermodal Freight under Uncertainty

Author

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  • Majbah Uddin

    (University of South Carolina)

  • Nathan Huynh

    (University of South Carolina)

Abstract

Transportation infrastructures, particularly those supporting intermodal freight, are vulnerable to natural disasters and man-made disasters that could lead to severe service disruptions. These disruptions can drastically degrade the capacity of a transportation mode and consequently have adverse impacts on intermodal freight transport and freight supply chain. To address service disruption, this paper develops a model to reliably route freight in a road-rail intermodal network. Specifically, the model seeks to provide the optimal route via road segments (highway links), rail segments (rail lines), and intermodal terminals for freight when the network is subject to capacity uncertainties. To ensure reliability, the model plans for reduced network link, node, and intermodal terminal capacity. A major contribution of this work is that a framework is provided to allow decision makers to determine the amount of capacity reduction to consider in planning routes to obtain a user-specified reliability level. The proposed methodology is demonstrated using a real-world intermodal network in the Gulf Coast, Southeastern, and Mid-Atlantic regions of the United States. It is found that the total system cost increases with the level of capacity uncertainty and with increased confidence levels for disruptions at links, nodes, and intermodal terminals.

Suggested Citation

  • Majbah Uddin & Nathan Huynh, 2019. "Reliable Routing of Road-Rail Intermodal Freight under Uncertainty," Networks and Spatial Economics, Springer, vol. 19(3), pages 929-952, September.
    • Handle: RePEc:kap:netspa:v:19:y:2019:i:3:d:10.1007_s11067-018-9438-6
    DOI: 10.1007/s11067-018-9438-6
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    3. Mohammad Tamannaei & Hamid Zarei & Sajede Aminzadegan, 2021. "A Game-Theoretic Approach to the Freight Transportation Pricing Problem in the Presence of Intermodal Service Providers in a Competitive Market," Networks and Spatial Economics, Springer, vol. 21(1), pages 123-173, March.
    4. Ning Li & Na Sun & Chunxia Cao & Shike Hou & Yanhua Gong, 2022. "Review on visualization technology in simulation training system for major natural disasters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(3), pages 1851-1882, July.
    5. Chunjiao Shao & Haiyan Wang & Meng Yu, 2022. "Multi-Objective Optimization of Customer-Centered Intermodal Freight Routing Problem Based on the Combination of DRSA and NSGA-III," Sustainability, MDPI, vol. 14(5), pages 1-25, March.
    6. Ginger Y. Ke, 2022. "Managing rail-truck intermodal transportation for hazardous materials with random yard disruptions," Annals of Operations Research, Springer, vol. 309(2), pages 457-483, February.
    7. Yan Sun & Xinya Li, 2019. "Fuzzy Programming Approaches for Modeling a Customer-Centred Freight Routing Problem in the Road-Rail Intermodal Hub-and-Spoke Network with Fuzzy Soft Time Windows and Multiple Sources of Time Uncerta," Mathematics, MDPI, vol. 7(8), pages 1-40, August.

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