A novel ordered weighted averaging weight determination based on ordinal dispersion

Abstract

One of the most common techniques to find the adequate weights in ordered weighted averaging (OWA) operators is based on the orness concept, where the weights are determined by maximizing the entropy (variation) for a fixed orness value. But such an entropy represents a dispersion measure for nominal variables, while weights in an OWA operator are essentially ordinal rather than nominal. Hence, in this paper, we propose a novel way to determine OWA weights based upon ordinal dispersion measures instead of an standard entropy measure. From this approach, we find an explicit formula for the weights, and we illustrate differences by means some multicriteria decision‐making examples.

Multiple Bipolar Fuzzy Measures: An Application to Community Detection Problems for Networks with Additional Information

“…So, we introduce two notions: extended multiple bipolar fuzzy graph and the bipolar weighted multi-graph associated with multiple bipolar fuzzy measures. Then, focusing on OWA operators [34][35][36][37], we propose several "group" notions, based on multiple bipolar fuzzy relations. Both elements will be crucial for dealing with community detection problems in which there is some additional information about the relation between the nodes given by multiple bipolar fuzzy measures.…”

“…Hence, the notion of a group will depend on the choice about these three operators. Particularly, we focus on the consideration of the ordered weighted averaging (OWA) AOs [34][35][36][37]. The most notable OWA operators are the maximum, the minimum, and the average.…”