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...

The determination of ordered weighted averaging (OWA) operator weights is a very important issue of applying the OWA operator for decision making. One of the first approaches, suggested by O’Hagan, determines a special class of OWA operators having maximal entropy of the OWA weights for a given level of orness; algorithmically it is based on the solution of a constrained optimization problem. I...

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...

Axiomatic generalizations of OWA operators are introduces and discussed. First, OMA operators based on comonotone modularity are recalled. Then, several kinds of comonotone pseudoadditivity based OWA generalizations are characterized and exemplified. Some of already known OWA generalizations are thus seen from new points of view. In several cases an integral representation of generalized OWA op...

Ordered weighted averaging (OWA) operators have been widely used in decision making these past few years. An important issue facing the OWA operators’ users is the determination of the OWA weights. This paper introduces an OWA determination method based on truncated distributions that enables intuitive generation of OWA weights according to a certain level of risk and trade-off. These two dimen...

In this work we deal with the problem of using OWA operators in color image reduction algorithms. For this reason, we study OWA operators defined on an arbitrary finite lattice endowed with a t-norm and a t-conorm. In the case of RGB color images, we apply OWA operators defined on a finite product lattice. Depending on the OWA operator considered, we see that the reduced images become brighter ...

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...