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On Consensus Measures in Fuzzy Group Decision Making

  • Conference paper
Modeling Decisions for Artificial Intelligence (MDAI 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5285))

Abstract

In group decision making problems, a natural question in the consensus process is how to measure the closeness among experts’ opinions in order to obtain the consensus level. To do so, different approaches have been proposed. For instance, several authors have introduced hard consensus measures varying between 0 (no consensus or partial consensus) and 1 (full consensus or complete agreement). However, consensus as a full and unanimous agreement is far from being achieved in real situations. So, in practice, a more realistic approach is to use softer consensus measures, which assess the consensus degree in a more flexible way. The aim of this paper is to identify the different existing approaches to compute soft consensus measures in fuzzy group decision making problems. Additionally, we analyze their advantages and drawbacks and study the future trends.

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Author information

Authors and Affiliations

  1. Dept. of Computer Science and Artificial Intelligence, University of Granada, 18071, Granada, Spain

    F. J. Cabrerizo, I. J. Pérez & E. Herrera-Viedma

  2. Dept. of Software Engineering, University of Granada, 18071, Granada, Spain

    S. Alonso

Authors
  1. F. J. Cabrerizo
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  2. S. Alonso
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  3. I. J. Pérez
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  4. E. Herrera-Viedma
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Editor information

Editors and Affiliations

  1. IIIA, Artificial Intelligence Research Institute CSIC, Spanish National Research Council,, Campus UAB s/n, 08193, Bellaterra, Catalonia, Spain

    Vicenç Torra

  2. Toho Gakuen,, 3-1-10 Naka, Kunitachi, 186-0004, Tokyo, Japan

    Yasuo Narukawa

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© 2008 Springer-Verlag Berlin Heidelberg

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Cabrerizo, F.J., Alonso, S., Pérez, I.J., Herrera-Viedma, E. (2008). On Consensus Measures in Fuzzy Group Decision Making. In: Torra, V., Narukawa, Y. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2008. Lecture Notes in Computer Science(), vol 5285. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88269-5_9

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  • DOI: https://doi.org/10.1007/978-3-540-88269-5_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88268-8

  • Online ISBN: 978-3-540-88269-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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