DocumentCode :
3625791
Title :
Decomposing Preference Relations
Author :
Daniel Gomez;Javier Montero;Javier Yanez
Author_Institution :
School of Statistics, Complutense University, Madrid, 28040 Spain. phone: +34 91 394 3994
fYear :
2007
fDate :
6/1/2007 12:00:00 AM
Firstpage :
1
Lastpage :
5
Abstract :
In this paper we address the problem of inconsistency in preference relations, pointing out the relevance of a meaningful representation in order to help decision maker to capture such inconsistencies. Dimension theory framework, despite its computational complexity, is considered here, pursuing in principle a decomposition of arbitrary preference relations in terms of linear orderings of alternatives. But we shall then stress that consistency should not be necessarily associated to a linear ordering. In this way, alternative decompositions of a preference relation can be proposed to decision maker, allowing an effective search for a useful representation of alternatives in terms of possible criteria. Such decompositions of our preference relations will then become the basis of a future decision aid model, always with the restricted aim of allowing the decision maker a better understanding of the problem. Inconsistencies may be not simply suppressed but understood, since they may contain relevant information.
Keywords :
"Decision making","Mathematics","Computational complexity","Stress","Mathematical analysis","Multidimensional systems","Fuzzy sets","Statistics","Context modeling","Legged locomotion"
Publisher :
ieee
Conference_Titel :
Fuzzy Systems Conference, 2007. FUZZ-IEEE 2007. IEEE International
ISSN :
1098-7584
Print_ISBN :
1-4244-1209-9
Type :
conf
DOI :
10.1109/FUZZY.2007.4295546
Filename :
4295546
Link To Document :
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