On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
A sequential selection process in group decision making with a linguistic assessment approach
Information Sciences—Intelligent Systems: An International Journal
Direct approach processes in group decision making using linguistic OWA operators
Fuzzy Sets and Systems
A model of consensus in group decision making under linguistic assessments
Fuzzy Sets and Systems
A new approach for ranking fuzzy numbers by distance method
Fuzzy Sets and Systems
A fusion approach for managing multi-granularity linguistic term sets in decision making
Fuzzy Sets and Systems
Distances between intuitionistic fuzzy sets
Fuzzy Sets and Systems
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
A method for group decision making with multi-granularity linguistic assessment information
Information Sciences: an International Journal
The collapsing method of defuzzification for discretised interval type-2 fuzzy sets
Information Sciences: an International Journal
An automatic approach to reaching consensus in multiple attribute group decision making
Computers and Industrial Engineering
A multi-granular linguistic model for management decision-making in performance appraisal
Soft Computing - A Fusion of Foundations, Methodologies and Applications
IEEE Transactions on Fuzzy Systems
Computing with words in decision making: foundations, trends and prospects
Fuzzy Optimization and Decision Making
IEEE Transactions on Knowledge and Data Engineering
The sampling method of defuzzification for type-2 fuzzy sets: Experimental evaluation
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Consensus reaching models of linguistic preference relations based on distance functions
Soft Computing - A Fusion of Foundations, Methodologies and Applications
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
OWA aggregation over a continuous interval argument with applications to decision making
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A consensus model for multiperson decision making with different preference structures
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Fuzzy Systems
A Consensus Model for Group Decision Making With Incomplete Fuzzy Preference Relations
IEEE Transactions on Fuzzy Systems
A Fuzzy Linguistic Methodology to Deal With Unbalanced Linguistic Term Sets
IEEE Transactions on Fuzzy Systems
A theoretical development on a fuzzy distance measure for fuzzy numbers
Mathematical and Computer Modelling: An International Journal
Minimum-Cost Consensus Models Under Aggregation Operators
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Information Sciences: an International Journal
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A crucial step in group decision making (GDM) processes is the aggregation of individual opinions with the aim of achieving a ''fair'' representation of each individual within the group. In multi-granular linguistic contexts where linguistic term sets with common domain but different granularity and/or semantic are used, the methodology widely applied until now requires, prior to the aggregation step, the application of a unification process. The reason for this unification process is the lack of appropriate aggregation operators for directly aggregating uncertain information represented by means of fuzzy sets. With the recent development of the Type-1 Ordered Weighted Averaging (T1OWA) operator, which is able to aggregate fuzzy sets, alternative approaches to multi-granular linguistic GDM problems are possible. Unlike consensus models based on unification processes, this paper presents a new T1OWA based consensus methodology that can directly manage linguistic term sets with different cardinality and/or semantic without the need to perform any transformation to unify the information. Furthermore, the linguistic information could be assumed to be balanced or unbalanced in its mathematical representation, and therefore the new T1OWA approach to consensus is more general in its application than previous consensus reaching processes with muti-granular linguistic information. To test the goodness of the new consensus reaching approach, a comparative study between the T1OWA based consensus model and the unification based consensus model is carried out using six randomly generated GDM problems with balanced multi-granular information. When distance between fuzzy sets used in the T1OWA based approach is defined as the corresponding distance between their centroids, a higher final level of consensus is achieved in four out of the six cases although no significant differences were found between both consensus approaches.