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Adaptive Intermodal Transportation for Freight Resilience: An Integrated and Flexible Strategy for Managing Disruptions

Author

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  • Siyavash Filom

    (Civil Engineering, McMaster University, Hamilton, ON L8S 4K1, Canada)

  • Satrya Dewantara

    (Civil Engineering and Geosciences, TU Delft, 2629 HS Delft, The Netherlands)

  • Mahnam Saeednia

    (Civil Engineering and Geosciences, TU Delft, 2629 HS Delft, The Netherlands)

  • Saiedeh Razavi

    (Civil Engineering, McMaster University, Hamilton, ON L8S 4K1, Canada)

Abstract

Background : Disruptions in freight transportation—such as service delays, infrastructure failures, and labor strikes—pose significant challenges to the reliability and efficiency of intermodal networks. To address these challenges, this study introduces Adaptive Intermodal Transportation (AIT), a resilient and flexible planning framework that enhances Synchromodal Freight Transport (SFT) by integrating real-time disruption management. Methods : Building on recent advances, we propose two novel strategies: (1) Reassign with Delay Buffer, which enables dynamic rerouting of shipments within a user-defined delay tolerance, and (2) (De)Consolidation, which allows splitting or merging of shipments across services depending on available capacity. These strategies are incorporated into a re-planning module that complements a baseline optimization model and a continuous disruption-monitoring system. Numerical experiments conducted on a Great Lakes-based case study evaluate the performance of the proposed strategies against a benchmark approach. Results : Results show that under moderate and high-disruption conditions, the proposed strategies reduce delay and disruption-incurred costs while increasing the percentage of matched shipments. The Reassign with Delay Buffer strategy offers controlled flexibility, while (De)Consolidation improves resource utilization in constrained environments. Conclusions : Overall, the AIT framework demonstrates strong potential for improving operational resilience in intermodal freight systems by enabling adaptive, disruption-aware planning decisions.

Suggested Citation

  • Siyavash Filom & Satrya Dewantara & Mahnam Saeednia & Saiedeh Razavi, 2025. "Adaptive Intermodal Transportation for Freight Resilience: An Integrated and Flexible Strategy for Managing Disruptions," Logistics, MDPI, vol. 9(3), pages 1-33, August.
  • Handle: RePEc:gam:jlogis:v:9:y:2025:i:3:p:107-:d:1719096
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    References listed on IDEAS

    as
    1. Filom, Siyavash & Razavi, Saiedeh, 2025. "A learning-based robust optimization framework for synchromodal freight transportation under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 195(C).
    2. Rentschler, J. & Elbert, R. & Weber, F., 2022. "Promoting Sustainability through Synchromodal Transportation: A Systematic Literature Review and Future Fields of Research," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 134691, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. Sakti, Sekar & Zhang, Lele & Thompson, Russell G., 2023. "Synchronization in synchromodality," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    4. He, Zhidong & Navneet, Kumar & van Dam, Wirdmer & Van Mieghem, Piet, 2021. "Robustness assessment of multimodal freight transport networks," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    5. Filom, Siyavash & Amiri, Amir M. & Razavi, Saiedeh, 2022. "Applications of machine learning methods in port operations – A systematic literature review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    6. Nasibeh Zanjirani Farahani & James Noble & Ronald Mcgarvey & Moein Enayati, 2023. "An advanced intermodal service network model for a practical transition to synchromodal transport in the US Freight System: A case study," Post-Print hal-04134439, HAL.
    7. Johannes Rentschler & Ralf Elbert & Felix Weber, 2022. "Promoting Sustainability through Synchromodal Transportation: A Systematic Literature Review and Future Fields of Research," Sustainability, MDPI, vol. 14(20), pages 1-22, October.
    8. Thibault Delbart & Yves Molenbruch & Kris Braekers & An Caris, 2021. "Uncertainty in Intermodal and Synchromodal Transport: Review and Future Research Directions," Sustainability, MDPI, vol. 13(7), pages 1-25, April.
    9. Jingling Zhang & Yusu Sun & Qinbing Feng & Yanwei Zhao & Zheng Wang & Qingling Wang, 2022. "Data-Driven Robust Optimization of the Vehicle Routing Problem with Uncertain Customers," Complexity, Hindawi, vol. 2022, pages 1-15, October.
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