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Low Probability---High Consequence Considerations in Routing Hazardous Material Shipments

Author

Listed:
  • Hanif D. Sherali

    (Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0118)

  • Laora D. Brizendine

    (P.O. Box 1043, Fairmont, WV 26555-1043)

  • Theodore S. Glickman

    (KPMG Peat Marwick, 2001 M Street, NW, Washington, DC 20036)

  • Shivaram Subramanian

    (Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0118)

Abstract

This paper is concerned with the development and analysis of a mathematical model for determining a route that attempts to reduce the risk of low probability---high consequence accidents related with the transportation of hazardous materials. The approach adopted considers trade-offs between the conditional expectation of a catastrophic outcome given that an accident has occurred, and more traditional measures of risk dealing with the expected value of the consequence and the accident probability on a selected path. More specifically, the problem we address involves finding a path that minimizes the conditional expectation objective value, subject to the expected value of the consequence being lesser than or equal to a specified value v , and the probability of an accident on the path being also constrained to be no more than some value (eta). The values v and (eta) are user-prescribed and could be prompted by the solution to the shortest path problems that minimize the respective corresponding linear risk functions. The proposed model is a discrete, fractional programming problem that is solved using a specialized branch-and-bound approach. A numerical example is provided for the sake of illustration, and some computational experience on randomly generated test cases is provided to study the effort required to solve this problem in different instances. The model is also tested using realistic data associated with a case concerned with routing hazardous materials through the roadways of Bethlehem, Pennsylvania. Data acquisition as well as algorithmic computational issues are discussed.

Suggested Citation

  • Hanif D. Sherali & Laora D. Brizendine & Theodore S. Glickman & Shivaram Subramanian, 1997. "Low Probability---High Consequence Considerations in Routing Hazardous Material Shipments," Transportation Science, INFORMS, vol. 31(3), pages 237-251, August.
    • Handle: RePEc:inm:ortrsc:v:31:y:1997:i:3:p:237-251
    DOI: 10.1287/trsc.31.3.237
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    Cited by:

    1. Soroush, H.M., 2008. "Optimal paths in bi-attribute networks with fractional cost functions," European Journal of Operational Research, Elsevier, vol. 190(3), pages 633-658, November.
    2. 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.
    3. Bronfman, Andrés & Marianov, Vladimir & Paredes-Belmar, Germán & Lüer-Villagra, Armin, 2016. "The maxisum and maximin-maxisum HAZMAT routing problems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 316-333.
    4. Madelynn R. D. Stackhouse & Robert Stewart, 2017. "Failing to Fix What is Found: Risk Accommodation in the Oil and Gas Industry," Risk Analysis, John Wiley & Sons, vol. 37(1), pages 130-146, January.
    5. Michael Bell, 2006. "Mixed Route Strategies for the Risk-Averse Shipment of Hazardous Materials," Networks and Spatial Economics, Springer, vol. 6(3), pages 253-265, September.
    6. 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.
    7. Yates, Justin & Sanjeevi, Sujeevraja, 2013. "A length-based, multiple-resource formulation for shortest path network interdiction problems in the transportation sector," International Journal of Critical Infrastructure Protection, Elsevier, vol. 6(2), pages 107-119.
    8. Erhan Erkut & Armann Ingolfsson, 2000. "Catastrophe Avoidance Models for Hazardous Materials Route Planning," Transportation Science, INFORMS, vol. 34(2), pages 165-179, May.
    9. Garrido, Rodrigo A. & Bronfman, Andrés C., 2017. "Equity and social acceptability in multiple hazardous materials routing through urban areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 244-260.
    10. Vaezi, Ali & Verma, Manish, 2018. "Railroad transportation of crude oil in Canada: Developing long-term forecasts, and evaluating the impact of proposed pipeline projects," Journal of Transport Geography, Elsevier, vol. 69(C), pages 98-111.
    11. Mohammadi, Mehrdad & Jula, Payman & Tavakkoli-Moghaddam, Reza, 2017. "Design of a reliable multi-modal multi-commodity model for hazardous materials transportation under uncertainty," European Journal of Operational Research, Elsevier, vol. 257(3), pages 792-809.
    12. 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).
    13. Altay, Nezih & Green III, Walter G., 2006. "OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 175(1), pages 475-493, November.

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