One of the new trends in genetic fuzzy systems (GFS) is the use of evolutionary multiobjective optimization (EMO) algorithms. This is because EMO algorithms can easily handle two conflicting objectives (i.e., accuracy maximization and complexity minimization) when we design accurate and compact fuzzy rule-based systems from numerical data. Since the main advantage of fuzzy rule-based systems co...

Information retrieval is the essential task for Traffic Information Service System in Intelligent Transportation Systems (ITS). There a lot of fuzzy traffic information derived from human factor. To achieve fuzzy semantic retrieval, this paper proposes an approach using Resource Description Framework (RDF) and fuzzy ontology. First, we apply RDF data model to represent traffic information on th...

The priority method of interval fuzzy preference relation is studied. A linear programming(LP) model based on multiplicative transitivity is constructed to derive interval weights from consistent or inconsistent interval fuzzy preference relation. By solving only one LP model, the proposed method can get the interval weights from an interval fuzzy preference relation, which can reduce the amoun...

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...

The problem of ®nding a solution set of alternatives when a linguistic preference relation represents a collective preference is analyzed following two research lines, choice functions and mechanisms. Four classical choice sets of alternatives for a linguistic preference relation are presented and some relations between them are pointed out. The concept of linguistic choice function as a tool t...

Transitivity is a very important property in order to provide coherence to a preference relation. Usually, t-norms are considered to define the transitivity of fuzzy relations. In this paper we deal with conjunctors, a wider family than t-norm, to define the transitivity. This more general definition allows to impove the results found in the literature. We characterize the behaviour with respec...

The problem of nding a solution set of alternatives when a linguistic preference relation represents a collective preference is analyzed following two research lines, choice functions and mechanisms. Four classical choice sets of alternatives for a linguistic preference relation are presented and some relations between them are pointed out. The concept of linguistic choice function as a tool to...

MCMD problems with fuzzy preference information on alternatives are essential problems of the importance of weighting and ranking. In this study, the AHP method is reviewed, and then Fuzzy PreRa and incomplete linguistic preference relations methods are elucidated. This study applied above three MCDM methods to a software selection problem proposed by Lai et al. [Software selection: a case stud...

Inspired by the idea of multiplicative intuitionistic preference relation (Xia MM et al. Preference relations based on intuitionistic multiplicative information, IEEE Transactions on Fuzzy Systems, 2013, 21(1): 113-133), in this paper, a new preference relation called the interval-valued multiplicative intuitionistic preference relation is developed. It is analyzed the basic operations for inte...

We propose a general scheme of collective choice rule that covers a number of well-known rules. Our point of departure is, first, the set of fuzzy preference relations, and second, the linguistic aggregation rule proposed by Kacprzyk [2-4]. We reconsider this rule on a more abstract level and use the OWA operators instead of Zadeh’s fuzzy linguistic quantifiers. All collective choice rules from...