IDEAS home Printed from https://ideas.repec.org/a/inm/ortrsc/v31y1997i3p237-251.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/trsc.31.3.237
    Download Restriction: no
    File URL: https://libkey.io/10.1287/trsc.31.3.237?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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).
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Erhan Erkut & Armann Ingolfsson, 2000. "Catastrophe Avoidance Models for Hazardous Materials Route Planning," Transportation Science, INFORMS, vol. 34(2), pages 165-179, May.
    11. 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.
    12. 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.
    13. 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.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ortrsc:v:31:y:1997:i:3:p:237-251. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.