A method for inference in approximate reasoning based on interval-valued fuzzy sets
Fuzzy Sets and Systems
Handling multicriteria fuzzy decision-making problems based on vague set theory
Fuzzy Sets and Systems
Interval valued strict preference with Zadeh triples
Fuzzy Sets and Systems - Special issue on fuzzy multiple criteria decision making
Vague sets are intuitionistic fuzzy sets
Fuzzy Sets and Systems
A fusion approach for managing multi-granularity linguistic term sets in decision making
Fuzzy Sets and Systems
Multicriteria fuzzy decision-making problems based on vague set theory
Fuzzy Sets and Systems
Multicriteria fuzzy decision-making methods based on intuitionistic fuzzy sets
Journal of Computer and System Sciences
Intuitionistic preference relations and their application in group decision making
Information Sciences: an International Journal
Clustering algorithm for intuitionistic fuzzy sets
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Intuitionistic fuzzy Choquet integral operator for multi-criteria decision making
Expert Systems with Applications: An International Journal
Intuitionistic Fuzzy Aggregation Operators
IEEE Transactions on Fuzzy Systems
Mathematical and Computer Modelling: An International Journal
Journal of Computer and System Sciences
Computers and Electronics in Agriculture
Information Sciences: an International Journal
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Hi-index | 12.05 |
The risk attitude of a decision maker is considered in the decision process. Inspired by mean-variance type utility functions in the financial risk management, a new class of decision functions are defined based on the weighted score function and the weighted accuracy function in the intuitionistic fuzzy setting. By choosing a suitable parameter value, the decision maker's risk attitude can be flexibly reflected by our decision function. The new method can be applied for both the exactly known and partly known criteria weight situations. For the latter case, it is only necessary to solve one linear programming problem. The developed models and algorithms are then extended to multiple criteria decision making problems with the interval-valued intuitionistic fuzzy information. Numerical examples are provided to illustrate the practicality, flexibility and efficiency of our new algorithms.