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Byline: Eduardo Fernandez (a), Jorge Navarro (a), Sergio Bernal (b)
Multicriteria classification; Fuzzy outranking relations; Parameter
elicitation; Evolutionary multiobjective optimization
Most multicriteria decision methods need the definition of a
significant amount of preferential information from a decision agent.
The preference disaggregation analysis paradigm infers the model's
parameter values from holistic judgments provided by a decision agent.
Here, a new method for inferring the parameters of a fuzzy outranking
model for multicriteria sorting is proposed. This approach allows us to
use most of the preferential information contained in a reference set.
The central idea is to characterize the quality of the model by
measuring discrepancies and concordances amongst (i) the preference
relations derived from the outranking model, and (ii) the preferential
information contained in the reference set. The model's parameters
are inferred from a multiobjective optimization problem, according to
some additional preferential information from a decision agent. Once the
model has been fitted, sorting decisions about new objects are performed
by using a fuzzy indifference relation. This proposal performs very well
in some examples.
(a) Autonomous University of Sinaloa, Culiacan, Sinaloa, Mexico
(b) CapitalI IQ, 55 Water Street 49th floor, New York, NY 10041,
Received 4 April 2007; Accepted 19 September 2008