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Planning and managing intermodal transportation of hazardous materials with capacity selection and congestion

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  • Assadipour, Ghazal
  • Ke, Ginger Y.
  • Verma, Manish

Abstract

The current literature in the rail–truck intermodal transportation of hazardous materials (hazmat) domain ignores congestion at intermodal yards. We attempt to close that gap by proposing a bi-objective optimization framework for managing hazmat freight that not only considers congestion at intermodal yards, but also determines the appropriate equipment capacity. The proposed framework, i.e., a non-linear MIP and a multi-objective genetic algorithm based solution methodology, is applied to a realistic size problem instance from existing literature. Our analysis indicates that terminal congestion risk is a significant portion of the network risk; and, that policies and tools involving number of cranes, shorter maximum waiting times, and tighter delivery times could have a positive bearing on risk.

Suggested Citation

  • Assadipour, Ghazal & Ke, Ginger Y. & Verma, Manish, 2015. "Planning and managing intermodal transportation of hazardous materials with capacity selection and congestion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 76(C), pages 45-57.
    • Handle: RePEc:eee:transe:v:76:y:2015:i:c:p:45-57
    DOI: 10.1016/j.tre.2015.02.003
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    Cited by:

    1. Zahra Fattahi & Javad Behnamian, 2022. "Location and transportation of intermodal hazmat considering equipment capacity and congestion impact: elastic method and sub-population genetic algorithm," Annals of Operations Research, Springer, vol. 316(1), pages 303-341, September.
    2. Aman Dua & Deepankar Sinha, 2019. "Assessment of Quality of Multimodal Transportation for Containerized Exports," IIM Kozhikode Society & Management Review, , vol. 8(1), pages 10-22, January.
    3. Ke, Ginger Y. & Verma, Manish, 2021. "A framework to managing disruption risk in rail-truck intermodal transportation networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    4. Victor M. Rayas & Marco A. Serrato, 2017. "A framework of the risk assessment for the supply chain of hazardous materials," Netnomics, Springer, vol. 18(2), pages 215-226, December.
    5. Mohri, Seyed Sina & Mohammadi, Mehrdad & Gendreau, Michel & Pirayesh, Amir & Ghasemaghaei, Ali & Salehi, Vahid, 2022. "Hazardous material transportation problems: A comprehensive overview of models and solution approaches," European Journal of Operational Research, Elsevier, vol. 302(1), pages 1-38.
    6. Nasrin Asgari & Mohsen Rajabi & Masoumeh Jamshidi & Maryam Khatami & Reza Zanjirani Farahani, 2017. "A memetic algorithm for a multi-objective obnoxious waste location-routing problem: a case study," Annals of Operations Research, Springer, vol. 250(2), pages 279-308, March.
    7. Ditta, A. & Figueroa, O. & Galindo, G. & Yie-Pinedo, R., 2019. "A review on research in transportation of hazardous materials," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    8. Zhang, Meng & Wang, Nengmin & He, Zhengwen & Jiang, Bin, 2021. "Vehicle routing optimization for hazmat shipments considering catastrophe avoidance and failed edges," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    9. Wu, Weitiao & Ma, Jian & Liu, Ronghui & Jin, Wenzhou, 2022. "Multi-class hazmat distribution network design with inventory and superimposed risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    10. Fang, Kan & Fu, Enyuan & Huang, Dian & Ke, Ginger Y. & Verma, Manish, 2025. "A value-at-risk based approach to the routing problem of multi-hazmat railcars," European Journal of Operational Research, Elsevier, vol. 320(1), pages 132-145.
    11. Bi, Mingkai & He, Shiwei & Xu, Wangtu (Ato), 2019. "Express delivery with high-speed railway: Definitely feasible or just a publicity stunt," Transportation Research Part A: Policy and Practice, Elsevier, vol. 120(C), pages 165-187.
    12. Baykasoğlu, Adil & Subulan, Kemal, 2016. "A multi-objective sustainable load planning model for intermodal transportation networks with a real-life application," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 207-247.
    13. Yang, Xin & Chen, Anthony & Ning, Bin & Tang, Tao, 2017. "Bi-objective programming approach for solving the metro timetable optimization problem with dwell time uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 22-37.
    14. Zajac, Sandra & Huber, Sandra, 2021. "Objectives and methods in multi-objective routing problems: a survey and classification scheme," European Journal of Operational Research, Elsevier, vol. 290(1), pages 1-25.
    15. Fang, Kan & Ke, Ginger Y. & Verma, Manish, 2017. "A routing and scheduling approach to rail transportation of hazardous materials with demand due dates," European Journal of Operational Research, Elsevier, vol. 261(1), pages 154-168.
    16. Song, Zhuzhu & Tang, Wansheng & Zhao, Ruiqing, 2020. "A simple game theoretical analysis for incentivizing multi-modal transportation in freight supply chains," European Journal of Operational Research, Elsevier, vol. 283(1), pages 152-165.
    17. Snežana Tadić & Milovan Kovač & Mladen Krstić & Violeta Roso & Nikolina Brnjac, 2021. "The Selection of Intermodal Transport System Scenarios in the Function of Southeastern Europe Regional Development," Sustainability, MDPI, vol. 13(10), pages 1-25, May.
    18. Zahiri, Behzad & Suresh, Nallan C., 2021. "Hub network design for hazardous-materials transportation under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    19. 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.
    20. Apichit Maneengam, 2023. "Multi-Objective Optimization of the Multimodal Routing Problem Using the Adaptive ε-Constraint Method and Modified TOPSIS with the D-CRITIC Method," Sustainability, MDPI, vol. 15(15), pages 1-22, August.
    21. Yan Sun & Xinya Li & Xia Liang & Cevin Zhang, 2019. "A Bi-Objective Fuzzy Credibilistic Chance-Constrained Programming Approach for the Hazardous Materials Road-Rail Multimodal Routing Problem under Uncertainty and Sustainability," Sustainability, MDPI, vol. 11(9), pages 1-27, May.
    22. Hilde Heggen & Yves Molenbruch & An Caris & Kris Braekers, 2019. "Intermodal Container Routing: Integrating Long-Haul Routing and Local Drayage Decisions," Sustainability, MDPI, vol. 11(6), pages 1-36, March.
    23. Archetti, Claudia & Peirano, Lorenzo & Speranza, M. Grazia, 2022. "Optimization in multimodal freight transportation problems: A Survey," European Journal of Operational Research, Elsevier, vol. 299(1), pages 1-20.
    24. Ghaderi, Abdolsalam & Burdett, Robert L., 2019. "An integrated location and routing approach for transporting hazardous materials in a bi-modal transportation network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 49-65.
    25. Shuxia Li & Yuedan Zu & Huimin Fang & Liping Liu & Tijun Fan, 2021. "Design Optimization of a HAZMAT Multimodal Hub-and-Spoke Network with Detour," IJERPH, MDPI, vol. 18(23), pages 1-18, November.

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