The problem of aggregating multiple numerical criteria to form overall objective functions is of considerable importance in many disciplines. The ordered weighted averaging (OWA) aggregation, introduced by Yager, uses the weights assigned to the ordered values rather than to the specific criteria. This allows one to model various aggregation preferences, preserving simultaneously the impartiali...

Yager @IEEE Trans Syst Man Cybern B 2004;34:1952–1963# introduced a continuous interval argument OWA ~C-OWA! operator, which extends the ordered weighted averaging ~OWA! operator, introduced by Yager @IEEE Trans Syst Man Cybern B 1988;18:183–190#, to the case in which the given argument is a continuous valued interval rather than a finite set of values. In this article, we utilize the C-OWA ope...

To achieve an effective and safe operation on the machine system where the human interacts with the machine mutually, there is a need for the machine to understand the human state, especially cognitive state, when the human’s operation task demands an intensive cognitive activity. Due to a well-known fact with the human being, a highly uncertain cognitive state and behavior as well as expressio...

Prior weights are necessary for the application of ordered weighted averaging (OWA) operators, but obtaining them is expensive and contentious, which restricts operators. To address weighting issue, weight space used to “replace” conventional vector, operator comparison then extended a partial order on space. The results show that OWA can be as long clear, is, there no need take accurate values...

The ordered weighted averaging (OWA) operator was developed by Yager [IEEE Trans. Syst., Man, Cybernet. 18 (1998) 183]. Later, Yager and Filev [IEEE Trans. Syst., Man, Cybernet.––Part B 29 (1999) 141] introduced a more general class of OWA operators called the induced ordered weighted averaging (IOWA) operators, which take as their argument pairs, called OWA pairs, in which one component is use...

The problem of aggregating multiple numerical attributes to form overall measure is of considerable importance in many disciplines. The ordered weighted averaging (OWA) aggregation, introduced by Yager, uses the weights assigned to the ordered values rather than to the specific attributes. This allows one to model various aggregation preferences, preserving simultaneously the impartiality (neut...

In this paper a class of combinatorial optimization problems with uncertain costs is discussed. The uncertainty is modeled by specifying a discrete scenario set containing K distinct cost scenarios. The Ordered Weighted Averaging (OWA for short) aggregation operator is applied to choose a solution. The well-known criteria such as: the maximum, minimum, average, Hurwicz and median are special ca...

The aim of this paper is to introduce a unified model between the generalized ordered weighted averaging (GOWA) operator and the generalized probabilistic aggregation. We present the generalized probabilistic OWA (GPOWA) operator. It is a new aggregation operator that unifies the probability with the OWA operator considering the degree of importance that each concept has in the analysis. It inc...

We study different types of aggregation operators such as the ordered weighted averaging (OWA) operator and the generalized OWA (GOWA) operator. We analyze the use of OWA operators in the Minkowski distance. We will call these new distance aggregation operator the Minkowski ordered weighted averaging distance (MOWAD) operator. We give a general overview of this type of generalization and study ...

This study surveys the Ordered Weighted Averaging (OWA) operator literature using a citation network analysis. The main goals are the historical reconstruction of scientific development of the OWA field, the identification of the dominant direction of knowledge accumulation that emerged since the publication of the first OWA paper and to discover the most active lines of research. The results s...