This article investigates multiplicative consistency ascertaining, inconsistency repairing, and weights derivation for hesitant preference relations (HMPRs). First, the completely weakly of HMPRs are defined. Based on them, 0–1 mixed programming models simple algebraic operations proposed to ascertain HMPRs. Then, some goal developed generate from consistent revise inconsistent An integrated pr...

In the resolution of a Multiperson Decision Making (MPDM) problem is usually important to assure that there is at least a certain level of agreement between the experts on the final solution. In this paper we present a Consensus Reaching Process for MPDM where the information given by the experts is based on incomplete fuzzy preference relations. In this process we define a method to generate a...

We introduce a model of menu choice in which a person’s psychological tastes and revealed preferences may be distinct. The former is modeled by means of a possibly incomplete (but otherwise rational) preference relation <, and the latter by a completion <∗ of that relation. The two relations are connected through an axiom which formalizes the following intuitive rule: “Whenever in doubt about w...

The original rough set model cannot be used to deal with the incomplete information systems. Nevertheless, by relaxing the indiscernibility relation to more general binary relations, many improved rough set models have been successfully applied into the incomplete information systems for knowledge acquisition. This article presents an explorative research focusing on the transition from incompl...

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...

We consider the problem of learning a user’s ordinal preferences on a multiattribute domain, assuming that her preferences are lexicographic. We introduce a general graphical representation called LP-trees which captures various natural classes of such preference relations, depending on whether the importance order between attributes and/or the local preferences on the domain of each attribute ...