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    Analyzing Consensus Measures in Group Decision Making

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    Author's copy of final accepted paper (184.6Kb)
    Date
    2015
    Author
    Chiclana, Francisco;
    Tapia García, Juan Miguel;
    del Moral, Maria Jose;
    Herrera-Viedma, Enrique
    Metadata
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    Abstract
    In Group Decision Making (GDM) problems before to obtain a solution a high level of consensus among experts is required. Consensus measures are usually built using similarity functions measuring how close experts’ opinions or preferences are. Similarity functions are defined based on the use of a metric describing the distance between experts’ opinions or preferences. In the literature, different distance functions have been proposed to implement consensus measures. This paper presents analyzes the effect of the application of some different distance functions for measuring consensus in GDM. By using the nonparametric Wilcoxon matched-pairs signed-ranks test, it is concluded that different distance functions can produce significantly different results. Moreover, it is also shown that their application also has a significant effect on the speed of achieving consensus. Finally, these results are analysed and used to derive decision support rules, based on a convergent criterion, that can be used to control the convergence speed of the consensus process using the compared distance functions.
    Description
    Citation : Chiclana, F. (2015) Analyzing Consensus Measures in Group Decision Making. Procedia Computer Science (The third International Conference on Information Technology and Quantitative Management - ITQM 2015).
    URI
    http://hdl.handle.net/2086/11021
    Research Group : Centre for Computational Intelligence
    Research Institute : Institute of Artificial Intelligence (IAI)
    Peer Reviewed : Yes
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    • School of Computer Science and Informatics [2970]

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