Fuzzy sets, decision making and expert systems
Fuzzy sets, decision making and expert systems
Advances in the Dempster-Shafer theory of evidence
Advances in the Dempster-Shafer theory of evidence
Handling multicriteria fuzzy decision-making problems based on vague set theory
Fuzzy Sets and Systems
Vague sets are intuitionistic fuzzy sets
Fuzzy Sets and Systems
Multicriteria fuzzy decision-making problems based on vague set theory
Fuzzy Sets and Systems
Uncertainty Models for Knowledge-Based Systems; A Unified Approach to the Measurement of Uncertainty
Uncertainty Models for Knowledge-Based Systems; A Unified Approach to the Measurement of Uncertainty
Multiattribute decision making models and methods using intuitionistic fuzzy sets
Journal of Computer and System Sciences
Multicriteria fuzzy decision-making methods based on intuitionistic fuzzy sets
Journal of Computer and System Sciences
Information Sciences: an International Journal
Information Sciences: an International Journal
Fuzzy Sets and Systems
Discussion: Some notes on (Atanassov's) intuitionistic fuzzy sets
Fuzzy Sets and Systems
On the representation of intuitionistic fuzzy t-norms and t-conorms
IEEE Transactions on Fuzzy Systems
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The main problem of known methods for Multiple Criteria Decision Making in the Intuitionistic Fuzzy setting is that they are generally based on the intermediate type reduction. Such approaches lead inevitable to the loss of important information. Another problem is the choice of an appropriate method for the local criteria aggregation taking into account their ranks. The aim of this paper is to present a new method which makes it possible to solve the first problem and facilitates the solution of the second one. The method is based on the Dempster-Shafer Theory (DST). It allows to solve the Multiple Criteria Decision Making problem without intermediate type reduction for different approaches to aggregation of the local criteria. The usefulness of elaborated method is illustrated with known example of Multiple Criteria Decision Making problem.