The paper introduces a new approach to preference structure, where from a weak preference relation derive the following relations:strict preference, indifference and incomparability, which by aggregations and negations are created and examined. We decomposing a preference relation into a strict preference, anindifference, and an incomparability relation.This approach allows one to quantify diff...

In Group Decision Making problems experts have to provide their preferences about some alternatives to solve a particular problem. Fuzzy Preference Relations are a very widely preference representation format that experts can use to express their opinions about the alternatives. But due to their own personal background and abilities experts are not often capable of provide complete and consiste...

In this paper, a new soft computing group decision method based on the concept of compromise ratio is introduced for determining decision makers (DMs)' weights through the group decision process under uncertainty. In this method, preferences and judgments of the DMs or experts are expressed by linguistic terms for rating the industrial alternatives among selected criteria as well as the relativ...

To address the situation where incomplete hesitant fuzzy preference relation (IHFPR) is necessary, this paper develops decision-making models taking into account decision makers’ satisfaction degree. First, consistency measures, respectively, from perspectives of additive and multiplicative consistent IHFPR are defined, which based on relationships IHPFRs their corresponding priority weight vec...

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...

Assuming a group decision making problem where the experts express their opinions by means of linguistic preference relations, the application of the Linguistic OWA operator guided by fuzzy majority is analyzed. Two diierent perspectives of the use of the LOWA operator are presented: (i) in the selection process, to aggregate individual linguistic preference relations in a collective one and to...

A fuzzy multipurpose decision making problem, where the information about the alternatives provided by the experts can be presented by means of diierent preference representation structures, is studied. Assuming that the information can be represented by means of preference orderings, utility functions and fuzzy preference relations, a general multipurpose decision making model is managed to co...

In [14] Yager and Filev introduced the Induced Ordered Weighted Averaging (IOWA) operator. In this paper, we provide some IOWA operators to aggregate fuzzy preference relations in group decision making problems. In particular, we present the Importance IOWA (I-IOWA) operator, the Consistency IOWA (C-IOWA) operator and the Preference IOWA (P-IOWA) operator. We also provide a procedure to deal wi...

We present a consensus model for group decision making with unbalanced fuzzy linguistic preference relations, i.e., assuming that the preferences are assessed on linguistic term sets whose terms are not symmetrically and uniformly distributed. This consensus model can manage incomplete information situations, that is, situations where the experts do not give all the preference values that they ...

Interval fuzzy preference relations can be useful to express decision makers' preferences in group decision-making problems. Usually, we apply a selection process and a consensus process to solve a group decision situation. In this paper, we present a consensus model for group decisionmaking problems with interval fuzzy preference relations. This model is based on two consensus criteria, a cons...