Interval valued intuitionistic fuzzy sets
Fuzzy Sets and Systems
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Optimization and Decision Making
Uncertainty modeling for database design using intuitionistic and rough set theory
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Information Sciences: an International Journal
Intuitionistic fuzzy Choquet integral operator for multi-criteria decision making
Expert Systems with Applications: An International Journal
Fuzzy Sets and Systems
Linear programming method for multiattribute group decision making using IF sets
Information Sciences: an International Journal
IEEE Transactions on Fuzzy Systems
Expert Systems with Applications: An International Journal
Computers & Mathematics with Applications
Multi-criteria decision-making method based on interval-valued intuitionistic fuzzy sets
Expert Systems with Applications: An International Journal
Induced generalized intuitionistic fuzzy operators
Knowledge-Based Systems
Expert Systems with Applications: An International Journal
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Recent progress in natural computation and knowledge discovery
Some results for dual hesitant fuzzy sets
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Statistical convergence of order β for generalized difference sequences of fuzzy numbers
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Triangular intuitionistic fuzzy numbers TIFNs are useful to deal with ill-known quantities in decision making problems. The focus of this paper is on multi-attribute decision making MADM problems in which the attribute values are expressed with TIFNs and the information on attribute weights is incomplete, which are solved by developing a new decision method based on possibility mean and variance of TIFNs. The notions of possibility mean and variance for TIFNs are introduced as well as the possibility standard deviation. A new ranking approach for TIFNs is developed according to the ratio of the possibility mean to the possibility standard deviation. Hereby we construct a bi-objective programming model, which maximizes the ratios of the possibility mean to the possibility standard deviation for membership and non-membership functions on alternative's overall attribute values. Using the lexicographic approach, the bi-objective programming model is transformed into two non-linear programming models, which are further transformed into the linear programming models by using the variable transformation. Thus, we can obtain the maximum ratios of the possibility mean to the possibility standard deviation, s are used to rank the alternatives. A numerical example is examined to demonstrate applicability and implementation process of the proposed method.