A New Consensus Model for Group Decision Making Problems With Non-Homogeneous Experts
By Ignacio Javier Pérez, F. Cabrerizo, Sergio Alonso, Enrique Herrera-Viedma. IEEE Transactions on Systems, Man & Cybernetics. Systems, 2014
340 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/a486c10de8606de6c84ea190e5aeb1ab8f8d3cf4
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Enrique Herrera-Viedma
- Francisco Chiclana
- Yucheng Dong
- Hengjie Zhang
- Jian Wu
- Francisco Herrera
- Hamido Fujita
- Luis Martínez-López
In Computational Theory and Mathematics
- Enrique Herrera-Viedma
- Francisco Chiclana
- Francisco Herrera
- Yucheng Dong
- Jian Wu
- Zeshui Xu
- Hengjie Zhang
- Luis Martínez-López
In Management Science and Operations Research
- Enrique Herrera-Viedma
- Francisco Chiclana
- Yucheng Dong
- Francisco Herrera
- Jian Wu
- Hengjie Zhang
- Hamido Fujita
- Zeshui Xu
Citations in the corpus
- The consensus models with interval preference opinions and their economic interpretation (2015, background): “Furthermore, the consensus model of the minimum cost and the maximum return with heterogeneous opinions [38] in GDM problems will also be taken into consideration in the future.”
- A visual interaction consensus model for social network group decision making with trust propagation (2017, background): “experts with a consensus level below a target threshold value, with advices on how to modify their preference values [23, 47].”
- Integrating experts' weights generated dynamically into the consensus reaching process and its applications in managing non-cooperative behaviors (2016, background): “Based on a “soft” consensus level, different types of CRPs have been proposed: (i) CRPs under different preference representation formats [10,13,15,17,28,35, 55]; (ii) CRPs with minimum adjustments or cost [5,6,12,16,22,23,66, 68,69]; (iii) CRPs based on consistency and consensus measures [18, 20,25”
- Fuzzy Group Decision Making With Incomplete Information Guided by Social Influence (2018, background): “∈ 𝐸 and implementing a specific aggregation operator, that appropriately takes into account such importance degrees in deriving the collective FPR [37]-[39].”
- Large-scale group decision making model based on social network analysis: Trust relationship-based conflict detection and elimination (2019, background): “at obtaining a collective solution as close as possible to unanimous agreement [6, 13, 14, 15, 16, 17, 18].”
- Multiple-Attribute Decision-Making Based on Archimedean Bonferroni Operators of q-Rung Orthopair Fuzzy Numbers (2019, methodology): “In further research, considering the superiority of new qROFS, we can study some of their fuzzy preference relations [28], [37]; we can also extend them to other some decision methods, such as TOPSIS method, VIKOR method, ELECTRE method, TODIM method, and so on, and apply them to deal with some prac”
- A minimum adjustment cost feedback mechanism based consensus model for group decision making under social network with distributed linguistic trust (2018, background): “Another issue to be addressed in GDM is the heterogeneous problem between group users [4, 33].”
- Trust based consensus model for social network in an incomplete linguistic information context (2015, methodology): “Consensus Index Key in the visual consensus model consists is the computation of the consensus index for each expert measuring the similarity between an expert’s provided preferences and the group of experts’ collective preferences [14, 41]: Level 1.”