Soft Consensus Models in Group Decision Making

Author(s):  
Ignacio Javier Perez ◽  
Francisco Javier Cabrerizo ◽  
Sergio Alonso ◽  
Francisco Chiclana ◽  
Enrique Herrera-Viedma
2010 ◽  
Vol 49 (3) ◽  
pp. 281-289 ◽  
Author(s):  
Yucheng Dong ◽  
Guiqing Zhang ◽  
Wei-Chiang Hong ◽  
Yinfeng Xu

2021 ◽  
Author(s):  
J.M. Tapia ◽  
F. Chiclana ◽  
M.J. Del Moral ◽  
E. Herrera-Viedma

In a Group Decision Making problem, several people try to reach a single common decision by selecting one of the possible alternatives according to their respective preferences. So, a consensus process is performed in order to increase the level of accord amongst people, called experts, before obtaining the final solution. Improving the consensus degree as much as possible is a very interesting task in the process. In the evaluation of the consensus degree, the measurement of the distance representing disagreement among the experts’ preferences should be considered. Different distance functions have been proposed to implement in consensus models. The Euclidean distance function is one of the most commonly used. This paper analyzes how to improve the consensus degrees, obtained through the Euclidean distance function, when the preferences of the experts are slightly modified by using one of the properties of the Uniform distribution. We fulfil an experimental study that shows the betterment in the consensus degrees when the Uniform extension is applied, taking into account different number of experts and alternatives.


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