Social choice axioms for fuzzy set aggregation
Fuzzy Sets and Systems - Special issue: Aggregation and best choices of imprecise opinions
Group decision making and consensus under fuzzy preferences and fuzzy majority
Fuzzy Sets and Systems - Special issue dedicated to Professor Claude Ponsard
Computers and Operations Research
Choice processes for non-homogeneous group decision making in linguistic setting
Fuzzy Sets and Systems
Fuzzy Sets and Systems - Special issue: Preference modelling and applications
On Compatibility of Interval Fuzzy Preference Relations
Fuzzy Optimization and Decision Making
Expert Systems with Applications: An International Journal
Consensus-based intelligent group decision-making model for the selection of advanced technology
Decision Support Systems
Fuzzy preference relations: Aggregation and weight determination
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
Induced ordered weighted averaging operators
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Aggregation operators for linguistic weighted information
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A consensus model for multiperson decision making with different preference structures
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Computers and Industrial Engineering
Hi-index | 12.05 |
Chiclana et al. [Chiclana, F., Herrera-Viedma, E., Herrera, F., Alonso, S. (2007). European Journal of Operational Research 182, 383-399] provided some IOWA operators for aggregating the individual fuzzy preference elations. The aim of this work is further to study their desired properties under group decision making problem with fuzzy preference relations. First, it is proved that the collective preference relations obtained by these cases of IOWA operators verified the reciprocity and the consistency properties. Next, the aggregation of individual judgements (AIJ) and the aggregation of individual priorities (AIP) provide the same priorities of alternatives by utilizing the IOWA operators as aggregation procedure and the row arithmetic mean method (RAMM) as prioritization procedure. Additionally, the Consistency IOWA (C-IOWA) operator guarantees that the group consistency degree is no less than the arithmetic mean of all the individual consistency degree. Finally, two illustrative numerical examples are used to verify the developed approaches.