This paper aims to establish the relationship between two apparent disparate problems: (i) the aggregation of uncertain information modelled by type-1 fuzzy sets via OWA mechanism, and (ii) the computation of the centroid of type-2 fuzzy sets. In order to cut down the computational complexity of the direct approach to performing type-1 OWA operation, the α-level approach to type-1 OWA operators...

The type-1 OWA operator is a new aggregation operator that is used to directly aggregate fuzzy sets via an OWA mechanism. In this paper, an α-level type-1 OWA operator capable of aggregating the α-cuts of fuzzy sets is proposed. Based on the fuzzy set Representation Theorem, we indicate that a general type-1 OWA operator can be represented by its α-level type-1 OWA operators. This result is ver...

We present the fuzzy induced generalized OWA (FIGOWA) operator. It is an aggregation operator that uses the main characteristics of the fuzzy OWA (FOWA) operator, the induced OWA (IOWA) operator and the generalized OWA (GOWA) operator. Therefore, it uses uncertain information represented in the form of fuzzy numbers, generalized means and order inducing variables. The main advantage of this ope...

We develop a new decision making model based on the use of a unified approach between the probability, the weighted average and the ordered weighted averaging (OWA) operator in an uncertain environment that can be assessed with fuzzy numbers (FNs). We present a new aggregation operator called the fuzzy probabilistic ordered weighted averaging – weighted averaging (FPOWAWA) operator. We study it...

Yager’s ordered weighted averaging (OWA) operator has been widely used in soft decision making to aggregate experts’ individual opinions or preferences for achieving an overall decision. The traditional Yager’s OWA operator focuses exclusively on the aggregation of crisp numbers. However, human experts usually tend to express their opinions or preferences in a very natural way via linguistic te...

Fuzzy Description Logics (Fuzzy DLs) are logics that allow to deal with structured knowledge affected by fuzziness. Fuzzy DLs are at the heart of Fuzzy OWL 2, a fuzzy version of the standard ontology language OWL 2. Although a relatively important amount of work has been carried out in the last years, fuzzy DLs are open to be extended with several features worked out in other fields. In particu...

This paper presents the fuzzy induced heavy ordered weighted averaging (FIHOWA) operator. It is an aggregation operator that uses the main characteristics of three well known aggregation operators: the heavy OWA, the induced OWA and the fuzzy OWA operator. Therefore, this operator provides a parameterized family of aggregation operators that includes the OWA operator and the total operator as s...

We consider different types of aggregation operators such as the heavy ordered weighted averaging (HOWA) operator and the fuzzy ordered weighted averaging (FOWA) operator. We introduce a new extension of the OWA operator called the fuzzy heavy ordered weighted averaging (FHOWA) operator. The main characteristic of this aggregation operator is that it deals with uncertain information represented...

This paper presents a new fuzzy group decision-making approach by using probabilities and ordered weighted averages (OWA). Thus, we are able to assess the problem considering probabilistic information and the attitudinal character of the decision maker. For doing so, the fuzzy generalized probabilistic OWA (FGPOWA) operator is presented. It is an aggregation operator that unifies the probabilit...

The OWA operator proposed by Yager has been widely used to aggregate experts’ opinions or preferences in human decision making. Yager’s traditional OWA operator focuses exclusively on the aggregation of crisp numbers. However, experts usually tend to express their opinions or preferences in a very natural way via linguistic terms. These linguistic terms can be modelled or expressed by (type-1) ...