Improving Euclidean's Consensus Degrees in Group Decision Making Problems Through a Uniform Extension

被引:0
作者
Tapia, J. M. [1 ]
Chiclana, F. [2 ]
Del Moral, M. J. [3 ]
Herrera-Viedma, E. [4 ]
机构
[1] Univ Granada, Dept Quantitat Methods, Granada, Spain
[2] De Montfort Univ, Dept Informat, Leicester, Leics, England
[3] Univ Granada, Granada, Spain
[4] Univ Granada, Dept Comp Sci & AI, Granada, Spain
来源
NEW TRENDS IN INTELLIGENT SOFTWARE METHODOLOGIES, TOOLS AND TECHNIQUES | 2021年 / 337卷
关键词
Group decision making; consensus; fuzzy preference relations; Euclidean distance; Uniform distribution;
D O I
10.3233/FAIA210033
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:343 / 350
页数:8
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