A web based consensus support system for group decision making problems and incomplete preferences

By Sergio Alonso, Enrique Herrera-Viedma, Francisco Chiclana, Francisco Herrera. Information Sciences, 2010

320 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/58f6c06d513b4f92f68f601c238e64a4b546caf9

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In Artificial Intelligence

In Computational Theory and Mathematics

In Management Science and Operations Research

Citations in the corpus

A minimum adjustment cost feedback mechanism based consensus model for group decision making under social network with distributed linguistic trust (2018, background): “, xn}, and by aggregating them into a collective one and applying a selection process a common solution is derived [1, 2, 34].”
Consistency Measures for Hesitant Fuzzy Linguistic Preference Relations (2014, unknown): “Another one is a feedback method [30]–[32], which generates suggestions for the DMs to help them change their preferences.”
A statistical comparative study of different similarity measures of consensus in group decision making (2013, methodology): “On the contrary, when the consensus level is acceptable, the moderator would apply a selection process in order to obtain the final consensus solution to the group decision making (GDM) problem [1, 27].”
A social network analysis trust-consensus based approach to group decision-making problems with interval-valued fuzzy reciprocal preference relations (2014, background): “In the procedure of group decision-making (GDM), experts usually need to compare a finite set of alternatives X = {x1, x2, . . . , xn} with respect to a single criterion, and construct preference relations.”
Integrating experts' weights generated dynamically into the consensus reaching process and its applications in managing non-cooperative behaviors (2016, background): “Usually, the consensus process is used to help experts improve the consensus level among the experts [1,9,34,52].”
A review of soft consensus models in a fuzzy environment (2014, background): “We should point out that the current consensus trends are committed to develop automated feedback mechanisms that replace the moderator, especially when consensus processes are developed in crowded social environments, such as Web 2.0 [59,60].”
A Consensus Model to Detect and Manage Noncooperative Behaviors in Large-Scale Group Decision Making (2014, background): “The commission must achieve a minimum level of agreement of μ = 0.85 before making a decision; the maximum number of rounds of discussion allowed is Maxround = 10, and the acceptability threshold is set as ε = 0.02.”