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Conditional value-at-risk (CVaR) methodology to optimal train configuration and routing of rail hazmat shipments

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  • Hosseini, S. Davod
  • Verma, Manish

Abstract

Hazardous materials (hazmat) incidents are rare though the consequences could be catastrophic. The low probability–high consequence nature of such events mandate that a risk-averse plan be implemented for routing hazmat shipments. We propose a conditional value-at-risk (CVaR) methodology for routing rail hazmat shipments, using the best train configuration, over a given railroad network using the pre-defined train services such that the transport risk as measured by CVaR is minimized. Freight train derailment records were analyzed to model the behavior of railroad accidents, and to estimate conditional probabilities. The proposed methodology was used to study several problem instances generated using the realistic network of a railroad operator, and to demonstrate that the proposed methodology is superior to other measures for risk-averse routing of hazmat shipments and versatile enough to yield routes based on risk preferences of the decision makers.

Suggested Citation

  • Hosseini, S. Davod & Verma, Manish, 2018. "Conditional value-at-risk (CVaR) methodology to optimal train configuration and routing of rail hazmat shipments," Transportation Research Part B: Methodological, Elsevier, vol. 110(C), pages 79-103.
    • Handle: RePEc:eee:transb:v:110:y:2018:i:c:p:79-103
    DOI: 10.1016/j.trb.2018.02.004
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    Cited by:

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    4. Jabbarzadeh, Armin & Azad, Nader & Verma, Manish, 2020. "An optimization approach to planning rail hazmat shipments in the presence of random disruptions," Omega, Elsevier, vol. 96(C).
    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. Liping Liu & Jiaming Li & Lei Zhou & Tijun Fan & Shuxia Li, 2021. "Research on Route Optimization of Hazardous Materials Transportation Considering Risk Equity," Sustainability, MDPI, vol. 13(16), pages 1-19, August.
    7. 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).
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    9. Tibor Sipos & Zsombor Szabó & Mohammed Obaid & Árpád Török, 2023. "Disaster Risk Assessment Scheme—A Road System Survey for Budapest," Sustainability, MDPI, vol. 15(8), pages 1-18, April.
    10. Huang, Wencheng & Zhang, Yue & Kou, Xingyi & Yin, Dezhi & Mi, Rongwei & Li, Linqing, 2020. "Railway dangerous goods transportation system risk analysis: An Interpretive Structural Modeling and Bayesian Network combining approach," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    11. Ghaffarinasab, Nader & Kara, Bahar Y., 2022. "A conditional β-mean approach to risk-averse stochastic multiple allocation hub location problems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    12. Vaezi Ali & Verma Manish, 2021. "Exploring an Infrastructure Investment Methodology to Risk Mitigation from Rail Hazardous Materials Shipments," Logistics, Supply Chain, Sustainability and Global Challenges, Sciendo, vol. 12(1), pages 1-16, December.
    13. Bhavsar, Nishit & Verma, Manish, 2022. "A subsidy policy to managing hazmat risk in railroad transportation network," European Journal of Operational Research, Elsevier, vol. 300(2), pages 633-646.
    14. Liu Su & Changhyun Kwon, 2020. "Risk-Averse Network Design with Behavioral Conditional Value-at-Risk for Hazardous Materials Transportation," Transportation Science, INFORMS, vol. 54(1), pages 184-203, January.
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