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Fuzzy risk analysis by similarity-based multi-criteria approach to classify alternatives

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Abstract

In this paper, a new method for fuzzy risk analysis based on similarity of fuzzy numbers is presented. First of all, the similarity-based multi-criteria approach is used to find the similarity between generalized trapezoidal fuzzy numbers and the desired fuzzy number to rank them. The geometry distance, spread difference, perimeter ratio, area ratio, and height ratio have been considered as criteria. Secondly, the proposed ranking approach is used for fuzzy risk analysis. Severity of loss, probability of failure, and failure ignorance possibility are the parameters to assess the risk of various alternatives. In the proposed fuzzy risk analysis, the alternatives can be classified into different levels in terms of their risk. Therefore, fuzzy risk analysis leads to classification and prioritization of the alternatives. Finally, a numerical example is presented to illustrate the applicability of the proposed method.

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Authors and Affiliations

  1. Faculty of Information Technology, Clayton campus, Monash University, Clayton, VIC, 3800, Australia

    Sanaz Nikfalazar

  2. School of Applied Sciences and Engineering, Faculty of Science, Monash University, Clayton, VIC, 3800, Australia

    Hadi Akbarzade Khorshidi

  3. Department of Industrial and System Engineering, Isfahan University of Technology, Isfahan, 84156-83111, Iran

    Ali Zeinal Hamadani

Authors
  1. Sanaz Nikfalazar
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  2. Hadi Akbarzade Khorshidi
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  3. Ali Zeinal Hamadani
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Correspondence to Hadi Akbarzade Khorshidi.

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Nikfalazar, S., Akbarzade Khorshidi, H. & Hamadani, A.Z. Fuzzy risk analysis by similarity-based multi-criteria approach to classify alternatives. Int J Syst Assur Eng Manag 7, 250–256 (2016). https://doi.org/10.1007/s13198-016-0414-6

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  • DOI: https://doi.org/10.1007/s13198-016-0414-6

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