A Comparative Study on Consensus Measures in Group Decision Making
In group decision making problems it is desirable to obtain a high level of consensus among experts before reaching a solution. It is customary to construct consensus measures by using similarity functions to quantify the closeness of experts preferences. In such process the use of a metric that describes the distance between experts preferences allows the definition of similarity and dissimilarity -distance- functions. Different distance functions have been proposed in order to implement consensus measures. This paper examines how the use of different aggregation operators affects the level of consensus achieved by experts through different distance functions, once the number of experts has been established in the decision making problem. The experimental study conducted states that the speed of the consensus process is significantly affected by the use of diverse aggregation operators and distance functions. Several decision support rules which can be useful in controling the convergence speed of the consensus process are also derived.
The file attached to this record is the author's final peer reviewed version.
Citation : del Moral M. J., Chiclana, F.,Tapia, J. M.,Herrera-Viedma, E. (2017) A Comparative Study on Consensus Measures in Group Decision Making. International Journal of Intelligent Systems.
ISSN : 1098-111X
Research Group : Centre for Computational Intelligence
Research Institute : Institute of Artificial Intelligence (IAI)
Peer Reviewed : Yes