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. Some well known criteria used in decision making under uncertainty such as the maximum, minimum, ...

In this paper, we look at the classical problem of aggregating individual utilities and study social orderings which are based on the concept of Ordered Weighted Averaging (OWA) Aggregating Operator. In these social orderings, called OWA social welfare functions (swf), weights are assigned a priori to the positions in the social ranking and, for every possible alternative, the total welfare is ...

A necessary and sufficient condition for the ordered weighted average (OWA) aggregation value of an arbitrary aggregated set to consistently increase with the orness level is proposed. The OWA operator properties associated with the orness level are extended. Then, with the generating function representation of Regular Increasing Monotone (RIM) quantifier, all these conditions and properties ar...

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...

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...

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...

Actual result of aggregation performed by an ordered weighted averaging (OWA) operator heavily depends upon the weighting vector used. A number of approaches for obtaining the associated weights have been suggested in the academic literature. In this paper, we present a method for determining the OWA weights when (1) the preferences of some subset of alternatives over other subset of alternativ...