@incollection{611,
  keywords = {Consensus},
  author = {Francisco Javier Cabrerizo and Francisco Chiclana and Ignacio Javier Pérez and Francisco Mata and Sergio Alonso and Enrique Herrera-Viedma},
  title = {A Feedback Mechanism Based on Granular Computing to Improve Consensus in GDM},
  abstract = {Group decision making is an important task in real world activities. It consists in obtaining the best solution to a particular problem according to the opinions given by a set of decision makers. In such a situation, an important issue is the level of consensus achieved among the decision makers before making a decision. For this reason, different feedback mechanisms, which help decision makers for reaching the highest degree of consensus possible, have been proposed in the literature. In this contribution, we present a new feedback mechanism based on granular computing to improve consensus in group decision making problems. Granular computing is a framework of designing, processing, and interpretation of information granules, which can be used to obtain a required flexibility to improve the level of consensus within the group of decision makers.},
  year = {2018},
  journal = {Soft Computing Applications for Group Decision-making and Consensus Modeling},
  volume = {357},
  chapter = {A Feedback Mechanism Based on Granular Computing to Improve Consensus in GDM},
  pages = {371-390},
  publisher = {Springer International Publishing},
  issn = {978-3-319-60206-6},
  isbn = {"978-3-319-60207-3"},
  url = {https://doi.org/10.1007/978-3-319-60207-3_22},
  doi = {10.1007/978-3-319-60207-3_22},
}