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Application of extended Dempster–Shafer theory of evidence in accident probability estimation for dangerous goods transportation

Author

Listed:
  • Yee Leung

    (The Chinese University of Hong Kong)

  • Rongrong Li

    (The Chinese University of Hong Kong)

  • Nannan Ji

    (Chang’an University)

Abstract

Transportation of dangerous goods (DGs) is generally associated with significant levels of risk. In the context of DG transportation, risk refers to the likelihood of incurring the undesirable consequences of a possible accident. Since the probability of an accident in a link of a route might depend on a variety of factors, it is necessary to find a way to combine the pieces of evidence/probabilities to estimate the composite probability for the link. Instead of using the Bayesian approach, commonly used in the literature, which requires decision-makers to estimate prior and conditional probabilities and cannot differentiate uncertainty from ignorance, this paper presents a novel approach based on the extended Dempster–Shafer theory of evidence by constructing an adaptive robust combination rule to estimate the accident probability under conflicting evidence. A case study is carried out for the transportation of liquefied petroleum gas in the road network of Hong Kong. Experimental results demonstrate the efficacy of the proposed approach.

Suggested Citation

  • Yee Leung & Rongrong Li & Nannan Ji, 2017. "Application of extended Dempster–Shafer theory of evidence in accident probability estimation for dangerous goods transportation," Journal of Geographical Systems, Springer, vol. 19(3), pages 249-271, July.
    • Handle: RePEc:kap:jgeosy:v:19:y:2017:i:3:d:10.1007_s10109-017-0253-2
    DOI: 10.1007/s10109-017-0253-2
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    References listed on IDEAS

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    1. Wu, Chong & Barnes, David, 2010. "Formulating partner selection criteria for agile supply chains: A Dempster-Shafer belief acceptability optimisation approach," International Journal of Production Economics, Elsevier, vol. 125(2), pages 284-293, June.
    2. Lianmeng Jiao & Quan Pan & Yan Liang & Xiaoxue Feng & Feng Yang, 2016. "Combining sources of evidence with reliability and importance for decision making," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 24(1), pages 87-106, March.
    3. Ehsan Ardjmand & Gary Weckman & Namkyu Park & Pooya Taherkhani & Manjeet Singh, 2015. "Applying genetic algorithm to a new location and routing model of hazardous materials," International Journal of Production Research, Taylor & Francis Journals, vol. 53(3), pages 916-928, February.
    4. Rongrong Li & Yee Leung, 2011. "Multi-objective route planning for dangerous goods using compromise programming," Journal of Geographical Systems, Springer, vol. 13(3), pages 249-271, September.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Accident probability estimation; Dangerous goods transportation; Dempster–Shafer theory of evidence;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • L92 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Railroads and Other Surface Transportation

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