A generalized OWA operator

Abstract

The ordered weighting averaging (OWA) Operator of Yager was introduced to provide a method for nonlinearly aggregating a set of input arguments ai. A fundamental aspect of the OWA operator is a reordering step in which the input arguments are rearranged according to their values. Recently, a generalized OWA operator was described in which each input argument ai has its own priority bi. The input arguments are then rearranged according to the priorities bi and not their values. Mitchell and Estrakh extended the generalized OWA by assuming the priorities are not known exactly. In this article we describe an alternative approach to include inexact priorities in the generalized OWA operator. Finally, we give a practical application of the new OWA operator to the problem of noise smoothing in an input picture. ©1999 John Wiley & Sons, Inc.

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