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Soft Computing

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01.03.2010 | Focus

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

verfasst von: F. J. Cabrerizo, J. M. Moreno, I. J. Pérez, E. Herrera-Viedma

Erschienen in: Soft Computing | Ausgabe 5/2010

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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.

Vorheriger Artikel Ordered weighted enhancement of preference modeling in the reference point method for multiple criteria optimization

Nächster Artikel Some relationships between Losonczi’s based OWA generalizations and the Choquet–Stieltjes integral

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Titel: Analyzing consensus approaches in fuzzy group decision making: advantages and drawbacks
verfasst von: F. J. Cabrerizo
J. M. Moreno
I. J. Pérez
E. Herrera-Viedma
Publikationsdatum: 01.03.2010
Verlag: Springer-Verlag
Erschienen in: Soft Computing / Ausgabe 5/2010
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-009-0453-x

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