Linguistic Measures Based on Fuzzy Coincidence for Reaching Consensus in Group Decision Making Herrera Triguero, Francisco Herrera Viedma, Enrique Verdegay Galdeano, José Luis Linguistic modeling Group decision-making Linguistic preference relations Consensus degrees Inteligencia artificial Artificial intelligence Assuming a linguistic framework, a model for the consensus reaching problem in heterogeneous group decision making is proposed. This model contains two types of linguistic consensus measures: linguistic consensus degrees and linguistic proximities to guide the consensus reaching process. These measures evaluate the current consensus state on three levels of action: level of the pairs of alternatives, level of the alternatives, and level of the relation. They are based on a fuzzy characterization of the concept of coincidence, and they are obtained by means of several conjunction functions for handling linguistic weighted information, the LOWA operator for aggregating linguistic information, and linguistic quantifiers representing the concept of fuzzy majority. 2022-11-10T08:20:41Z 2022-11-10T08:20:41Z 1997 journal article F. Herrera, E. Herrera-Viedma, J.L. Verdegay, Linguistic measures based on fuzzy coincidence for reaching consensus in group decision making, International Journal of Approximate Reasoning, Volume 16, Issues 3–4, 1997, Pages 309-334, ISSN 0888-613X, [https://doi.org/10.1016/S0888-613X(96)00121-1] https://hdl.handle.net/10481/77869 10.1016/S0888-613X(96)00121-1 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Elsevier