IDEAS home Printed from https://ideas.repec.org/a/kap/jgeosy/v19y2017i3d10.1007_s10109-017-0253-2.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10109-017-0253-2
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10109-017-0253-2?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    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)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Majchrzak Joanna & Goliński Marek & Mantura Władysław, 2020. "The concept of the qualitology and grey system theory application in marketing information quality cognition and assessment," 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. 28(2), pages 817-840, June.
    2. Zajac, Sandra & Huber, Sandra, 2021. "Objectives and methods in multi-objective routing problems: a survey and classification scheme," European Journal of Operational Research, Elsevier, vol. 290(1), pages 1-25.
    3. Jiu-Ying Dong & Shu-Ping Wan, 2016. "Virtual enterprise partner selection integrating LINMAP and TOPSIS," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(10), pages 1288-1308, October.
    4. Misagh Rahbari & Alireza Arshadi Khamseh & Yaser Sadati-Keneti & Mohammad Javad Jafari, 2022. "A risk-based green location-inventory-routing problem for hazardous materials: NSGA II, MOSA, and multi-objective black widow optimization," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(2), pages 2804-2840, February.
    5. Costantino, Nicola & Dotoli, Mariagrazia & Falagario, Marco & Fanti, Maria Pia & Mangini, Agostino Marcello, 2012. "A model for supply management of agile manufacturing supply chains," International Journal of Production Economics, Elsevier, vol. 135(1), pages 451-457.
    6. Nasrin Asgari & Mohsen Rajabi & Masoumeh Jamshidi & Maryam Khatami & Reza Zanjirani Farahani, 2017. "A memetic algorithm for a multi-objective obnoxious waste location-routing problem: a case study," Annals of Operations Research, Springer, vol. 250(2), pages 279-308, March.
    7. Wang, Juyoung & Cevik, Mucahit & Amin, Saman Hassanzadeh & Parsaee, Amir Ali, 2021. "Mixed-integer linear programming models for the paint waste management problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
    8. Zahra Fattahi & Javad Behnamian, 2022. "Location and transportation of intermodal hazmat considering equipment capacity and congestion impact: elastic method and sub-population genetic algorithm," Annals of Operations Research, Springer, vol. 316(1), pages 303-341, September.
    9. Rabbani, M. & Heidari, R. & Yazdanparast, R., 2019. "A stochastic multi-period industrial hazardous waste location-routing problem: Integrating NSGA-II and Monte Carlo simulation," European Journal of Operational Research, Elsevier, vol. 272(3), pages 945-961.
    10. Lin Zhou & Xu Wang & Lin Ni & Yun Lin, 2016. "Location-Routing Problem with Simultaneous Home Delivery and Customer’s Pickup for City Distribution of Online Shopping Purchases," Sustainability, MDPI, vol. 8(8), pages 1-20, August.
    11. Guertler, Benjamin & Spinler, Stefan, 2015. "Supply risk interrelationships and the derivation of key supply risk indicators," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 224-236.
    12. Mohri, Seyed Sina & Asgari, Nasrin & Zanjirani Farahani, Reza & Bourlakis, Michael & Laker, Benjamin, 2020. "Fairness in hazmat routing-scheduling: A bi-objective Stackelberg game," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    13. Chao Fu & Min Xue & Wenjun Chang, 2022. "Multiple criteria decision making with reliability of assessment," Annals of Operations Research, Springer, vol. 312(1), pages 121-157, May.
    14. Rongrong Li & Yee Leung & Hui Lin & Bo Huang, 2013. "An adaptive compromise programming method for multi-objective path optimization," Journal of Geographical Systems, Springer, vol. 15(2), pages 211-228, April.
    15. Zhong, Shaopeng & Cheng, Rong & Jiang, Yu & Wang, Zhong & Larsen, Allan & Nielsen, Otto Anker, 2020. "Risk-averse optimization of disaster relief facility location and vehicle routing under stochastic demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    16. Sadeghi, Mohammad & Yaghoubi, Saeed, 2024. "Optimization models for cloud seeding network design and operations," European Journal of Operational Research, Elsevier, vol. 312(3), pages 1146-1167.
    17. Tasneem Bani-Mustafa & Nicola Pedroni & Enrico Zio & Dominique Vasseur & Francois Beaudouin, 2020. "A hierarchical tree-based decision-making approach for assessing the relative trustworthiness of risk assessment models," Journal of Risk and Reliability, , vol. 234(6), pages 748-763, December.
    18. Guertler, Benjamin & Spinler, Stefan, 2015. "When does operational risk cause supply chain enterprises to tip? A simulation of intra-organizational dynamics," Omega, Elsevier, vol. 57(PA), pages 54-69.
    19. Bei Lyu & Hui Chen, 2022. "Effect of Founder Control on Equity Financing and Corporate Performance-Based on Moderation of Radical Strategy," SAGE Open, , vol. 12(2), pages 21582440221, April.
    20. Hao Wang & Quan Liu & Hongyang Zhang & Yinlong Jin & Wenzhen Yu, 2022. "A Two-Stage Decision-Making Method Based on WebGIS for Bulk Material Transportation of Hydropower Construction," Energies, MDPI, vol. 15(5), pages 1-21, February.

    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

    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:kap:jgeosy:v:19:y:2017:i:3:d:10.1007_s10109-017-0253-2. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.