Deriving a final ranking from fuzzy preferences: An approach compatible with the Principle of Correspondence

Up to now, classical decision models and fuzzy approaches for decision-making have been seen as mutually inconsistent proposals. Based on bivalent 0–1 logic, classical decision-making approaches should be particular cases of decision models which consider fuzzy preferences. Here, a new method for deriving a final prescription from a fuzzy preference relation is proposed, which satisfies the so-called Principle of Correspondence. This proposal is more robust than others in relation to irrelevant alternatives, minimizing contradictions between the final prescription and the global model of a decision-maker’s preferences previously captured in a fuzzy outranking relation. The resulting complex multiobjective optimization problem is solved by using an operational evolutionary algorithm.