Aggregation of group fuzzy risk information in the railway risk decision making process

Min An, Y Qin, L Jia, Yao Chen

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29 Citations (Scopus)
106 Downloads (Pure)


Railway risk assessment is a hierarchical process where risk information obtained at lower levels may be used for risk assessment at higher levels. Fuzzy analytical hierarchy process (FAHP) is widely used in risk decision making process to solve imprecise hierarchical problems where the risk data are incomplete or there is a high level of uncertainty involved in the risk data, particularly, in the process of railway safety and risk decision making. However, the application of FAHP in risk decision making the risk analysts often face the circumstances where a large number of pairwise comparison matrices have to be established by
expert knowledge and engineering judgements. There may be a lack of confidence that all comparisons associated with a railway system are completely justified in a rigorous way. This is particularly true when a complex railway system needs to be analysed or when subjective judgements should be involved. This paper presents a modified FAHP approach that employs fuzzy multiplicative consistency method for the establishment of pairwise comparison matrices in risk decision making analysis. The use of the proposed method yields a higher level of confidence that all of comparisons associated with the system are
justified. In the meanwhile, the workload in determining the consistency of the judgements can be reduced significantly. A case example is used to demonstrate the proposed methodology. The results indicate that by using the proposed method, risks associated with a railway system can be assessed effectively and efficiently, and more reliable and accurate results can be obtained.
Original languageEnglish
Pages (from-to)18-28
Number of pages11
JournalSafety Science
Early online date14 Sept 2015
Publication statusPublished - Feb 2016


  • Railway risk assessment
  • Decision making
  • Expert and engineering judgement
  • Multiplicative preference relation
  • Fuzzy multiplicative consistency


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