In some MCDM techniques Ð most notably in Outranking Methods Ð the result of the comparison of a finite set of alternatives according to several criteria is summarised using a fuzzy preference relation. This fuzzy relation does not, in general, possess "nice properties" such as transitivity or completeness and elaborating a recommendation on the basis of such information is not an obvious task....

In many practical situation, some of the attribute values for an object may be interval and set-valued. This paper introduces the interval and set-valued information systems and decision systems. According to the semantic relation of attribute values, interval and set-valued information systems can be classified into two categories: disjunctive (Type 1) and conjunctive (Type 2) systems. In this...

Aiming at configuration design for mass customization, this paper develops a fuzzy ranking methodology for concept evaluation. The fuzzy preference relation is applied to modeling the fuzziness on the level of a single criterion as well as on a global level. The ranking approach integrates linguistic terms and fuzzy numbers into the fuzzy preference model so as to characterize both intangible a...

This paper suggests  a novel approach for ranking the most applicable fuzzy numbers, i.e.  $LR$-fuzzy numbers. Applying the  $alpha$-optimistic values of a fuzzy number, a preference criterion is proposed for ranking fuzzy numbers using the Credibility index. The main properties of the proposed  preference criterion  are also studied.  Moreover, the proposed method is   applied for ranking fuzz...

We consider multiple agent settings where each agent reports a partial preference order. We derive a condition, called the TSinterval order property, on the underlying fuzzy weak preference relation which, when satisfied, yields an interval order on the set of alternatives. We then propose a greedy algorithm to aggregate those interval orders.

Einstein product and Einstein sum are good alternatives to the algebraic product and algebraic sum, respectively. Nevertheless, it seems that in the literature there is little investigation on aggregation techniques using the Einstein operations on IFS for aggregating a collection of intuitionistic fuzzy value (IFV). The induced ordered weighted averaging operator is more suitable for aggregati...

This contribution proposes a technique for Fuzzy Rule Based Classification Systems (FRBCSs) based on a multi-classifier approach using fuzzy preference relations for dealing with multi-class classification. The idea is to decompose the original data-set into binary classification problems using a pairwise coupling approach (confronting all pair of classes), and to obtain a fuzzy system for each...

Revealed preference theory was initiated by Samuelson [8] as a way of defining the rational behaviour of a consumer in terms of a preference relation associated with a demand function. This topic has been axiomatically treated by Arrow (1959), Richter (1966), Sen (1971) and many others. Papers Banerjee (1995), Georgescu (2004; 2005) attempt at developing a theory of revealed preference for fuzz...

This article presents a new fuzzy multiple criteria decision making model for the evaluation of airline competitiveness over a period. The evaluation problem is formulated as a fuzzy multiple criteria decision making problem and solved by our strength-weakness based approach. For finding out the strength and weakness of an airline over another airline, we present a preference function based on ...

In this paper, we propose a dominance-based rough set approach for the decision analysis of a preference-ordered uncertain data table, which is comprised of a finite set of objects described by a finite set of criteria. The domains of the criteria may have ordinal properties that express preference scales. In the proposed approach, we first compute the degree of dominance between any two object...