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Assessing Risks Through the Determination of Rare Event Probabilities

Author

Listed:
  • Allan R. Sampson

    (University of Pittsburgh, Pittsburgh, Pennsylvania)

  • Robert L. Smith

    (University of Michigan, Ann Arbor, Michigan)

Abstract

We consider the problem of evaluating the probability of occurrence of rare, but potentially catastrophic, events. The lack of historical data renders conventional statistical approaches inappropriate. The problem is compounded by complex multivariate dependencies that may exist across potential event sites. In order to evaluate the likelihood of one or more such catastrophic events occurring, we provide an information theoretic model for merging a decision maker's opinion with expert judgment. Also provided is a methodology for the reconciling of conflicting expert judgments. This merging approach is invariant to the decision maker's viewpoint in the limiting case of exceptionally rare events. These methods are applied to likelihood assessment of liquid natural gas tanker spills and seismic induced light water nuclear reactor meltdowns.

Suggested Citation

  • Allan R. Sampson & Robert L. Smith, 1982. "Assessing Risks Through the Determination of Rare Event Probabilities," Operations Research, INFORMS, vol. 30(5), pages 839-866, October.
    • Handle: RePEc:inm:oropre:v:30:y:1982:i:5:p:839-866
    DOI: 10.1287/opre.30.5.839
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    Citations

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    Cited by:

    1. Donald E. Brown & Robert L. Smith, 1990. "A correspondence principle for relative entropy minimization," Naval Research Logistics (NRL), John Wiley & Sons, vol. 37(2), pages 191-202, April.
    2. Shuo Zeng & Moshe Dror, 2019. "Serving many masters: an agent and his principals," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 90(1), pages 23-59, August.
    3. David Simchi-Levi & William Schmidt & Yehua Wei & Peter Yun Zhang & Keith Combs & Yao Ge & Oleg Gusikhin & Michael Sanders & Don Zhang, 2015. "Identifying Risks and Mitigating Disruptions in the Automotive Supply Chain," Interfaces, INFORMS, vol. 45(5), pages 375-390, October.
    4. de la Torre, Luis E. & Dolinskaya, Irina S. & Smilowitz, Karen R., 2012. "Disaster relief routing: Integrating research and practice," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 88-97.
    5. Johannes G. Jaspersen & Gilberto Montibeller, 2015. "Probability Elicitation Under Severe Time Pressure: A Rank‐Based Method," Risk Analysis, John Wiley & Sons, vol. 35(7), pages 1317-1335, July.
    6. Lydia Novoszel & Tina Wakolbinger, 2022. "Meta-analysis of Supply Chain Disruption Research," SN Operations Research Forum, Springer, vol. 3(1), pages 1-25, March.
    7. 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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