Applied Intelligence

, Volume 50, Issue 1, pp 157–168 | Cite as

Fuzzy risk analysis under influence of non-homogeneous preferences elicitation in fiber industry

  • Ahmad Syafadhli Abu BakarEmail author
  • Ku Muhammad Naim Ku Khalif
  • Asma Ahmad Shariff
  • Alexander Gegov
  • Fauzani Md Salleh


Fuzzy risk analysis plays an important role in mitigating the levels of harm of a risk. In real world scenarios, it is a big challenge for risk analysts to make a proper and comprehensive decision when coping with risks that are incomplete, vague and fuzzy. Many established fuzzy risk analysis approaches do not have the flexibility to deal with knowledge in the form of preferences elicitation which lead to incorrect risk decision. The inefficiency is reflected when they consider only risk analyst preferences elicitation that is partially known. Nonetheless, the preferences elicited by the risk analyst are often non-homogeneous in nature such that they can be completely known, completely unknown, partially known and partially unknown. In this case, established fuzzy risk analysis methods are considered as inefficient in handling risk, hence an appropriate fuzzy risk analysis method that can deal with the non-homogeneous nature of risk analyst’s preferences elicitation is worth developing. Therefore, this paper proposes a novel fuzzy risk analysis method that is capable to deal with the non-homogeneous risk analyst’s preferences elicitation based on grey numbers. The proposed method aims at resolving the uncertain interactions between homogeneous and non-homogeneous natures of risk analyst’s preferences elicitation by using a novel consensus reaching approach that involves transformation of grey numbers into grey parametric fuzzy numbers. Later on, a novel fuzzy risk assessment score approach is presented to correctly evaluate and distinguish the levels of harm of the risks faced, such that these evaluations are consistent with preferences elicitation of the risk analyst. A real world risk analysis problem in fiber industry is then carried out to demonstrate the novelty, validity and feasibility of the proposed method.


Fuzzy risk analysis Grey numbers Non-homogeneous preferences elicitation Fiber industry 



This research work is funded by University of Malaya Research Grants BK061-2016 and RF001H-2018 and Malaysia Ministry of Education Research Grant FRGS/1/2018/STG06/UM/02/14.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Ahmad Syafadhli Abu Bakar
    • 1
    • 2
    Email author
  • Ku Muhammad Naim Ku Khalif
    • 3
  • Asma Ahmad Shariff
    • 1
    • 2
  • Alexander Gegov
    • 4
  • Fauzani Md Salleh
    • 5
  1. 1.Mathematics Division, Centre for Foundation Studies in ScienceUniversity of MalayaKuala LumpurMalaysia
  2. 2.Centre of Research for Computational Sciences and Informatics in Biology, Bioindustry, Environment, Agriculture and Healthcare (CRYSTAL)University of MalayaKuala LumpurMalaysia
  3. 3.Department of Science Program (Mathematics), Faculty of Industrial Sciences and TechnologyUniversiti Malaysia PahangGambangMalaysia
  4. 4.School of ComputingUniversity of PortsmouthPortsmouthUK
  5. 5.Chemistry Division, Centre for Foundation Studies in ScienceUniversity of MalayaKuala LumpurMalaysia

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