Fuzzy risk analysis based on a geometric ranking method for generalized trapezoidal fuzzy numbers

Abstract

In this study, we present a new method for ranking generalized trapezoidal fuzzy numbers based on the incenter and inradius of a triangle. The proposed method is simple and easy to apply to real life problems. The method can also rank crisp numbers and fuzzy numbers with the same centroid point. Some comparative examples are also given to illustrate the advantages of the proposed method. Based on the proposed ranking method, we also give an application to the fuzzy risk analysis problem.

Fuzzy risk analysis based on Ochiai ranking index with Hurwicz criterion for generalized trapezoidal fuzzy numbers

“…The ranking result of the proposed method is similar with Sets 2 and 3 which is affected by decision makers' perspective. For Set 6, the ranking result of the proposed method is consistent with all the existing methods except [4] and [1].…”

“…The ranking result is affected by decision makers' perspective which shows that the proposed method has a strong discrimination ability. The pessimistic decision makers produce three different ranking results with is consistent with [4], [5], [14], [7], [6], [8] and [1].…”

“…In this section, the proposed ranking method is applied in dealing with FRA problem. Assume 1 A , The proposed FRA algorithm is presented as follows:…”

“…[8] further presented a ranking method based on the left and right height. Recently, [1] presented a geometric ranking method for handling with FRA problems.…”

A short note on methods of ranking fuzzy numbers in risk analysis problems

“…Numerous studies have indicated that fuzzy tools are becoming very popular in risk analysis problems because of the flexibility and efficiency they give to a decision maker (e.g. Chen and Chen, 2008;Akyar et al, 2013;Madhuri et al, 2014 andAlidoosti et al, 2012).…”