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
fDate :
6/1/2007 12:00:00 AM
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"
Conference_Titel :
Fuzzy Systems Conference, 2007. FUZZ-IEEE 2007. IEEE International
Print_ISBN :
1-4244-1209-9
DOI :
10.1109/FUZZY.2007.4295546