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Soft Computing

, Volume 14, Issue 5, pp 451–463 | Cite as

Analyzing consensus approaches in fuzzy group decision making: advantages and drawbacks

  • F. J. CabrerizoEmail author
  • J. M. Moreno
  • I. J. Pérez
  • E. Herrera-Viedma
Focus

Abstract

Two processes are necessary to solve group decision making problems: a consensus process and a selection process. The consensus process is necessary to obtain a final solution with a certain level of agreement between the experts, while the selection process is necessary to obtain such a final solution. Clearly, it is preferable that the set of experts reach a high degree of consensus before applying the selection process. In order to measure the degree of consensus, different approaches have been proposed. For example, we can use hard consensus measures, which vary between 0 (no consensus or partial consensus) and 1 (full consensus), or soft consensus measures, which assess the consensus degree in a more flexible way. The aim of this paper is to analyze the different consensus approaches in fuzzy group decision making problems and discuss their advantages and drawbacks. Additionally, we study the future trends.

Keywords

Group decision making Consensus process Soft consensus measures Future trends 

Notes

Acknowledgements

This paper has been developed with the financing of the SAINFOWEB project (TIC00602), Feder Funds in FUZZYLING project (TIN2007-61079) and PETRI project (PET 2007-0460).

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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • F. J. Cabrerizo
    • 1
    Email author
  • J. M. Moreno
    • 2
  • I. J. Pérez
    • 3
  • E. Herrera-Viedma
    • 3
  1. 1.Department of Software Engineering and Computer SystemsDistance Learning University of SpainMadridSpain
  2. 2.Department of Information and Communication EngineeringUniversity of MurciaMurciaSpain
  3. 3.Department of Computer Science and Artificial IntelligenceUniversity of GranadaGranadaSpain

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