8 This article investigates the consistency of interval fuzzy preference relations based on interval 9 arithmetic, and new definitions are introduced for additive consistent, multiplicative consistent 10 and weakly transitive interval fuzzy preference relations. Transformation functions are put 11 forward to convert normalized interval weights into consistent interval fuzzy preference relations...

We introduce two criteria for judging “goodness” of the result when combining preference relations in information systems: completeness and consistency. Completeness requires that the result must be the union of all preference relations, while consistency requires that the result must be an acyclic relation. In other words, completeness requires that the result contain all pairs appearing in th...

Intuitionistic preference relations are becoming increasingly important in the field of group decision making since they present a flexible and simple way to the experts to provide their preference relations, while at the same time allowing them to accommodate a certain degree of hesitation inherent to all decision making processes. In this contribution, we prove the mathematical equivalence be...

In this paper, we investigate group decision making problems with multiple types of linguistic preference relations. The paper has two parts with similar structures. In the first part, we transform the uncertain additive linguistic preference relations into the expected additive linguistic preference relations, and present a procedure for group decision making based on multiple types of additiv...

In this paper we consider some properties of intuitionistic fuzzy preference relations. We pay attention to preservation of intuitionistic fuzzy preference relations by aggregation operations. In particular, we know, that a special kind of aggregation operations (lattice operations) do not preserve intuitionistic fuzzy preference relations. We describe the operations which preserve intuitionist...

We introduce two criteria for judging “goodness” of the result when combining preference relations in information systems: completeness and consistency. Completeness requires that the result must be the union of all preference relations, while consistency requires that the result must be an acyclic relation. In other words, completeness requires that the result contain all pairs appearing in th...

In decision making, consistency in fuzzy preference relations is associated with the study of transitivity property. While using additive consistency property to complete incomplete preference relations, the preference values found may lie outside the interval [0, 1] or the resultant relation may itself be inconsistent. This paper proposes a method that avoids inconsistency and completes an inc...

In this paper we summarize some results on constructing preference relations from criterion values, in the framework of multiple criteria decision making. First we recall two types of methods to build a comprehensive preference model. Then we show how to construct crisp and fuzzy preferences from criterion evaluations.

Changing preferences is very common in real life. The expressive power of the operations of preference change introduced so far in the literature is limited to adding new information about preference and equivalence. Here, we discuss the operation of discarding preferences: preference contraction. We argue that the property of minimality and the preservation of strict partial orders are crucial...

Preference analysis is an important task in multi-criteria decision making. The rough set theory has been successfully extended to deal with preference analysis by replacing equivalence relations with dominance relations. The existing studies involving preference relations cannot capture the uncertainty presented in numerical and fuzzy criteria. In this paper, we introduce a method to extract f...