Paper Info
Title
An adaptive consensus support model for group decision-making problems in a multigranular fuzzy linguistic context
Abstract
Different consensus models for group decision-making (GDM) problems have been proposed in the literature. However, all of them consider the consensus reaching process a rigid or inflexible one because its behavior remains fixed in all rounds of the consensus process. The aim of this paper is to improve the consensus reaching process in GDM problems defined in multigranular linguistic contexts, i.e., by using linguistic term sets with different cardinality to represent experts' preferences. To do that, we propose an adaptive consensus support system model for this type of decision-making problem, i.e., a process that adapts its behavior to the agreement achieved in each round. This adaptive model increases the convergence toward the consensus and, therefore, reduces the number of rounds to reach it.
Year
DOI
Venue
2009
10.1109/TFUZZ.2009.2013457
IEEE T. Fuzzy Systems
Keywords
Field
DocType
multigranular fuzzy linguistic context,adaptive model,gdm problem,adaptive consensus support model,different consensus model,different cardinality,multigranular linguistic context,consensus process,linguistic term set,group decision-making,adaptive consensus support system,group decision-making problem,decision-making problem,group decision making,context modeling,artificial intelligence,adaptive systems,computer science,convergence,fuzzy set theory,consensus
Convergence (routing),Adaptive system,Fuzzy logic,Cardinality,Fuzzy set,Context model,Artificial intelligence,Uniform consensus,Linguistics,Machine learning,Mathematics,Group decision-making
Journal
Volume
Issue
ISSN
17
2
1063-6706
Citations 
PageRank 
References 
193
4.96
46
Authors
4
Search Limit
100193
Name
Order
Citations
PageRank
F. Mata173023.63
Luis Martínez2174767.16
Enrique Herrera-Viedma313105642.24
Herrera-Viedma, E.41975.37