This article introduces the uncertain ordered weighted averaging adequacy coefficient (UOWAAC) operator. novel operator uses (OWA) operator, coefficient, and interval numbers in a single formulation. also extends UOWAAC by using order-inducing variables reordering process of input arguments. new extension is called induced (UIOWAAC) The presents an application approach multi-criteria group deci...

The ordered weighted averaging (OWA) operator 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 impartiality (neutrality) with respect to the individual attributes. The determination of ordered weighted averaging (OWA) operator weights is a crucial issue of applying the OW...

Customer segmentation involves an identification of distinct customer groups. Traditionally, customers were segmented by some criteria such as location, type of business, and customer value. In this paper we determine a methodology for identifying appropriate customer segments by using customer satisfaction-demanding behavior that is characterized by the disparity of derived global satisfaction...

This paper concerns with rank-dependent poverty measures and shows that an ordered weighted averaging, hereafter OWA, operator is underlying in the definition of these indices. The dual decomposition of an OWA operator into the self-dual core and the anti-self-dual remainder allows us to propose a decomposition for all the rank-dependent poverty measures in terms of incidence, intensity and ine...

This paper presents an efficient fuzzy neural system which consists of modular neural networks combined by the fuzzy integral with ordered weighted averaging (OWA) operators. The ability of the fuzzy integral to combine the results of multiple sources of information has been established in seL'eral preL'ious works. The key point of this paper is to formalize modular neural networks as informati...

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...

We study multiple referenda and committee elections, when the ballot of each voter is simply a set of approved binary issues (or candidates). Two well-known rules under this model are the commonly used candidate-wise majority, also called the minisum rule, as well as the minimax rule. In the former, the elected committee consists of the candidates approved by a majority of voters, whereas the l...

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...

The assessment of goods quality using experts is costly task in addition to their often unavailability. In this paper, we present a new method for ranking physical features of consumer goods according to their relevancy to multiple evaluators’ perception at different levels and selecting the most important ones for quality characterization. The main contribution of the paper is combining of fuz...