We introduce a new aggregation operator called the heavy ordered weighted averaging – weighted averaging (HOWAWA) operator. It is a new aggregation operator that uses the weighted average and the ordered weighted average in the same formulation and considering the degree of importance that each concept has in the analysis. Moreover, by using heavy aggregations, we are allowing the weighting vec...

We develop a new model for decision making under risk environment and under uncertainty. We introduce a new aggregation operator that unifies the probabilities and the ordered weighted averaging (OWA) operator in the same formulation. We call it the probabilistic ordered weighted averaging (POWA) operator. This aggregation operator provides a more complete representation of the decision problem...

In this paper a class of bottleneck combinatorial optimization problems with uncertain costs is discussed. The uncertainty is modeled by specifying a discrete scenario set containing a finite number of cost vectors, called scenarios. In order to choose a solution the Ordered Weighted Averaging aggregation operator (shortly OWA) is applied. The OWA operator generalizes traditional criteria in de...

Abstract An IFS is suitable way to deal with uncertainty, but operators on it are complex in computation even though they work well. This study presents a C-OWA operator-based method to make aggregation over intuitionistic fuzzy information more easy and convenient, and then applies it to complicated decision making under uncertainty. IFNs or IIFNs are transformed into intervals which are easy ...

Recently, in (Loyer & Straccia 2005) the Any-World Assumption (AWA) has been introduced for normal logic programs as a generalization of the well-known notions of Closed World Assumption (CWA) and the Open World Assumption (OWA). The AWA allows any assignment (i.e. interpretation), over a truth space (bilattice), to be a default assumption and, thus, the CWA and OWA are just special cases. Whil...

We study different types of aggregation operators. We focus on the generalized OWA (GOWA) operator developed by Yager which represents a generalization to a wide range of aggregation operators. We distinguish between aggregations with a descending or with an ascending order. We introduce the induced generalized OWA (IGOWA) operator which represents an extension to the GOWA operator. It generali...

This paper deals with the characterization of two classes of monotonic and neutral (MN) aggregation operators . The first class corresponds to (MN) aggregators which are stable for the same positive linear transformations and present the ordered linkage property. The second class deals with (MN)-idempotent aggregators which are stable for positive linear transformations with same unit, independ...

The Minkowski distance is a distance measure that generalizes a wide range of other distances such as the Hamming and the Euclidean distance. In this paper, we develop a generalization of the Minkowski distance by using the induced ordered weighted averaging (IOWA) operator. We will call it the induced Minkowski OWA distance (IMOWAD). Then, we are able to obtain a wider range of distance measur...

We propose a least absolute deviation model for obtaining OWA operator weights: Minimize ∑i=n−1 i=1 |wi − wi−1| subject to orness(W ) = ∑n i=1 n−i n−1wi = α, 0 ≤ α ≤ 1, w1 + · · ·+ wn = 1, 0 ≤ wi, i = 1, · · · , n. Recently, the extended minimax disparity problem was proved by Hong [Fuzzy Sets and Systems, 168 (2011) 35-46]. In this paper, we investigated the equivalence of the solutions for th...

The methods for determining OWA operator weights have aroused wide attention. We first review the main existing methods for determining OWA operator weights. We next introduce the principle of maximum entropy for setting up probability distributions on the basis of partial knowledge and prove that Xu’s normal distribution-based method obeys the principle of maximum entropy. Finally, we propose ...