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Value-at-Risk model for hazardous material transportation

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  • Yingying Kang
  • Rajan Batta
  • Changhyun Kwon

Abstract

This paper introduces a Value-at-Risk (VaR) model to generate route choices for a hazmat shipment based on a specified risk confidence level. VaR is a threshold value such that the probability of the loss exceeding the VaR value is less than a given probability level. The objective is to determine a route which minimizes the likelihood that the risk will be greater than a set threshold. Several properties of the VaR model are established. An exact solution procedure is proposed and tested to solve the single-trip problem. To test the applicability of the approach, routes obtained from the VaR model are compared with those obtained from other hazmat objectives, on a numerical example as well as a hazmat routing scenario derived from the Albany district of New York State. Depending on the choice of the confidence level, the VaR model gives different paths from which we conclude that the route choice is a function of the level of risk tolerance of the decision-maker. Further refinements of the VaR model are also discussed. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Yingying Kang & Rajan Batta & Changhyun Kwon, 2014. "Value-at-Risk model for hazardous material transportation," Annals of Operations Research, Springer, vol. 222(1), pages 361-387, November.
    • Handle: RePEc:spr:annopr:v:222:y:2014:i:1:p:361-387:10.1007/s10479-012-1285-0
    DOI: 10.1007/s10479-012-1285-0
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    4. Chiou, Suh-Wen, 2018. "A traffic-responsive signal control to enhance road network resilience with hazmat transportation in multiple periods," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 105-118.
    5. Shahrzad Faghih-Roohi & Yew-Soon Ong & Sobhan Asian & Allan N. Zhang, 2016. "Dynamic conditional value-at-risk model for routing and scheduling of hazardous material transportation networks," Annals of Operations Research, Springer, vol. 247(2), pages 715-734, December.
    6. Bogyrbayeva, Aigerim & Kwon, Changhyun, 2021. "Pessimistic evasive flow capturing problems," European Journal of Operational Research, Elsevier, vol. 293(1), pages 133-148.
    7. Boon Ean Teoh & S. G. Ponnambalam & Nachiappan Subramanian, 2018. "Data driven safe vehicle routing analytics: a differential evolution algorithm to reduce CO $$_{2}$$ 2 emissions and hazardous risks," Annals of Operations Research, Springer, vol. 270(1), pages 515-538, November.
    8. 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.
    9. Oleksandr Romanko & Helmut Mausser, 2016. "Robust scenario-based value-at-risk optimization," Annals of Operations Research, Springer, vol. 237(1), pages 203-218, February.
    10. 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.
    11. Kumar, Anand & Roy, Debjit & Verter, Vedat & Sharma, Dheeraj, 2018. "Integrated fleet mix and routing decision for hazmat transportation: A developing country perspective," European Journal of Operational Research, Elsevier, vol. 264(1), pages 225-238.
    12. Oleksandr Romanko & Helmut Mausser, 2016. "Robust scenario-based value-at-risk optimization," Annals of Operations Research, Springer, vol. 237(1), pages 203-218, February.
    13. Liping Liu & Qing Wu & Shuxia Li & Ying Li & Tijun Fan, 2021. "Risk Assessment of Hazmat Road Transportation Considering Environmental Risk under Time-Varying Conditions," IJERPH, MDPI, vol. 18(18), pages 1-19, September.
    14. Arman Saeidi & Soroush Aghamohamadi-Bosjin & Masoud Rabbani, 2021. "An integrated model for management of hazardous waste in a smart city with a sustainable approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(7), pages 10093-10118, July.
    15. 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.
    16. 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.

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