One of the most important issues in the theory of OWA operators is the determination of associated weights. This matter is essential in order to use the best-suited OWA operator in each aggregation process. Given that some aggregation processes can be seen as extensions of majority rules to the field of gradual preferences, it is possible to determine the OWA operator weights by taking into acc...

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...

In this article we extend the similarity classifier to cover also Ordered Weighted Averaging (OWA) operators. Earlier, similarity classifier was mainly used with generalized mean operator, but in this article we extend this aggregation process to cover more general OWA operators. With OWA operators we concentrate on linguistic quantifier guided aggregation where several different quantifiers ar...

Commonly used GIS combination operators such as Boolean conjunction/disjunction and weighted linear combination can be generalized to the ordered weighted averaging (OWA) family of operators. This multicriteria evaluation method allows decision-makers to define a decision strategy on a continuum between pessimistic and optimistic strategies. Recently, OWA has been introduced to GIS-based decisi...

In this paper we prove that, under suitable conditions, Atanassov’s Ka operators, which act on intervals, provide the same numerical results as OWA operators of dimension two. On one hand, this allows us to recover OWA operators from Ka operators. On the other hand, by analyzing the properties of Atanassov’s operators, we can generalize them. In this way, we introduce a class of aggregation fun...

We analyze different types of aggregation operators. We focus on the generalized OWA (GOWA) operator and the Quasi-OWA operator which generalize a wide range of aggregation operators. We also analyze a recent approach that unifies the weighted average and the OWA operator in the same formulation called ordered weighted averaging – weighted averaging (OWAWA) operator. We introduce the fuzzy gene...

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...

This paper explores the use of the optimization procedures in SAS/OR software with application to the ordered weighted averaging (OWA) operators of decision-making. OWA was originally introduced by Yager (1988) has gained much interest among researchers, hence many applications in the areas of decision making, expert systems, data mining, approximate reasoning, fuzzy system and control have bee...

This paper will introduce a new method to obtain the order weightsof the Ordered Weighted Averaging (OWA) operator. We will first show therelation between fuzzy quantifiers and neat OWA operators and then offer anew combination of them. Fuzzy quantifiers are applied for soft computingin modeling the optimism degree of the decision maker. In using neat operators,the ordering of the inputs is not...