Ranking fuzzy numbers with index of optimism
Fuzzy Sets and Systems
Decision criteria for computer-aided parting surface design
Computer-Aided Design
Ranking fuzzy numbers with integral value
Fuzzy Sets and Systems
A new approach for ranking fuzzy numbers by distance method
Fuzzy Sets and Systems
Ranking multi-criterion river basin planning alternatives using fuzzy numbers
Fuzzy Sets and Systems
Ranking fuzzy numbers based on decomposition principle and signed distance
Fuzzy Sets and Systems - Special issue on fuzzy numbers and uncertainty
Reasonable properties for the ordering of fuzzy quantities (I)
Fuzzy Sets and Systems
Reasonable properties for the ordering of fuzzy quantities (II)
Fuzzy Sets and Systems
The revised method of ranking fuzzy numbers with an area between the centroid and original points
Computers & Mathematics with Applications
A new approach for ranking of trapezoidal fuzzy numbers
Computers & Mathematics with Applications
Computers & Mathematics with Applications
Ranking L-R fuzzy number based on deviation degree
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Centroid defuzzification and the maximizing set and minimizing set ranking based on alpha level sets
Computers and Industrial Engineering
Area ranking of fuzzy numbers based on positive and negative ideal points
Computers & Mathematics with Applications
On the centroids of fuzzy numbers
Fuzzy Sets and Systems
The revised method of ranking LR fuzzy number based on deviation degree
Expert Systems with Applications: An International Journal
Ranking of fuzzy numbers by sign distance
Information Sciences: an International Journal
Intuitionistic fuzzy multi-criteria decision-making method based on evidential reasoning
Applied Soft Computing
Parting curve selection and evaluation using an extension of fuzzy MCDM approach
Applied Soft Computing
An improved ranking method for fuzzy numbers with integral values
Applied Soft Computing
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A large number of methods have been proposed for ranking fuzzy numbers in the last few decades. Nevertheless, none of these methods can always guarantee a consistent result for every situation. Some of them are even non-intuitive and not discriminating. Chen proposed a ranking method in 1985 to overcome these limitations and simplify the computational procedure based on the criteria of total utility through maximizing set and minimizing set. However, there were some shortcomings associated with Chen's ranking method. Therefore, we propose a revised ranking method that can overcome these shortcomings. Instead of considering just a single left and a single right utility in the total utility, the proposed method considers two left and two right utilities. In addition, the proposed method also takes into account the decision maker's optimistic attitude of fuzzy numbers. Several comparative examples and an application demonstrating the usage, advantages, and applicability of the revised ranking method are presented. It can be concluded that the revised ranking method can effectively resolve the issues with Chen's ranking method. Moreover, the revised ranking method can be used to differentiate different types of fuzzy numbers.