Paper Info
Title
Two-layer weight large group decision-making method based on multi-granularity attributes.
Abstract
To overcome the information ambiguity inherent in multi-attribute large group decision-making problems, an interval 2-tuple linguistic large group decision-making method based on multi-granularity attributes is proposed. Considering the preferences of individual decision makers, the group is clustered and classified to form an aggregate structure. The two-layer weight model is developed from the decision makers' different contribution to the existing clusters' and different contribution of different clusters. The possible degree formula for expansion is used to calculate the weighted value of the decision makers in all clusters. Fuzzy entropy is used to confirm the weighted value of each cluster, and the fuzzy relative entropy is then used to sort the schemes. Finally, an illustrative example indicates that the proposed model is feasible and effective for large group decision-making.
Year
DOI
Venue
2017
10.3233/JIFS-152590
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
Keywords
Field
DocType
Multi-granularity attributes,two-layer weight,large group decision-making
Artificial intelligence,Granularity,Mathematics,Machine learning,Group decision-making
Journal
Volume
Issue
ISSN
33
3
1064-1246
Citations 
PageRank 
References 
0
0.34
23
Authors
4
Name
Order
Citations
PageRank
Xuanhua Xu11227.46
Qian Sun22810.81
Bin Pan3279.99
Bingsheng Liu41778.56