Ranking fuzzy numbers with index of optimism
Fuzzy Sets and Systems
Ranking fuzzy numbers with integral value
Fuzzy Sets and Systems
An index for ordering fuzzy numbers
Fuzzy Sets and Systems
Evaluating weapon systems using fuzzy arithmetic operations
Fuzzy Sets and Systems
A probabilistic approach to rank complex fuzzy numbers
Fuzzy Sets and Systems
Ranking and defuzzification methods based on area compensation
Fuzzy Sets and Systems
A new method for tool steel materials selection under fuzzy environment
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
Ranking fuzzy numbers by preference ratio
Fuzzy Sets and Systems
Fuzzy Multiple Attribute Decision Making: Methods and Applications
Fuzzy Multiple Attribute Decision Making: Methods and Applications
Comparison of fuzzy numbers using a fuzzy distance measure
Fuzzy Sets and Systems - Fuzzy intervals
The revised method of ranking fuzzy numbers with an area between the centroid and original points
Computers & Mathematics with Applications
Ranking fuzzy numbers with an area method using radius of gyration
Computers & Mathematics with Applications
Ranking nonnormal p-norm trapezoidal fuzzy numbers with integral value
Computers & Mathematics with Applications
A new approach for ranking of trapezoidal fuzzy numbers
Computers & Mathematics with Applications
Ranking L-R fuzzy number based on deviation degree
Information Sciences: an International Journal
Ranking fuzzy numbers with preference weighting function expectations
Computers & Mathematics with Applications
Ranking of fuzzy numbers by sign distance
Information Sciences: an International Journal
A method for ranking fuzzy numbers and its application to decision-making
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Hybrid pattern search and simulated annealing for fuzzy production planning problems
Computers & Mathematics with Applications
Approximations of fuzzy numbers by trapezoidal fuzzy numbers preserving the ambiguity and value
Computers & Mathematics with Applications
Linguistic cost-sensitive learning of genetic fuzzy classifiers for imprecise data
International Journal of Approximate Reasoning
Advances in Fuzzy Systems
A revised method for ranking fuzzy numbers using maximizing set and minimizing set
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
Analyzing the ranking method for L-R fuzzy numbers based on deviation degree
Computers and Industrial Engineering
An improved ranking method for fuzzy numbers with integral values
Applied Soft Computing
Fuzzy risk analysis based on a geometric ranking method for generalized trapezoidal fuzzy numbers
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Ranking function of two LR-fuzzy numbers
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Hi-index | 0.09 |
The maximizing set and minimizing set method is a popular ranking approach for fuzzy numbers, which ranks them based on their left, right and total utilities. This paper presents an alternative ranking approach for fuzzy numbers called area ranking based on positive and negative ideal points, which defines two new alternative indices for the purpose of ranking. The two new indices are defined in terms of a decision maker (DM)'s attitude towards risks and the left and the right areas between fuzzy numbers and the two ideal points. It is shown that the area ranking approach has strong discrimination power and can rank fuzzy numbers that are unable to be discriminated by the maximizing set and minimizing set method. It is also shown that the DM's attitude towards risks may have a significant impact on the ranking of fuzzy numbers. As a side product, a new defuzzification formula is also developed and discussed.