Distance measures in ordered weighted averaging (OWA) operators allow the modelling of complex decision making problems where a set ideal values or characteristics are required to be met. The objective this paper is introduce extended distance and logarithmic OWA-based especially designed for analysis financial investment options. Based on immediate weights, Bonferroni means operators, we weigh...

The type-1 ordered weighted averaging (T1OWA) operator has demonstrated the capacity for directly aggregating multiple sources of linguistic information modeled by fuzzy sets rather than crisp values. Yager's (OWA) operators possess properties idempotence, monotonicity, compensativeness, and commutativity. This article aims to address whether or not T1OWA these when inputs associated weights ar...

The ordered weighted averaging (OWA) operator is one of the most used techniques in operator’s aggregation procedure. This paper proposes a new assignment algorithm by using OWA and different extensions it Branch-and-bound algorithm. process based on use average distance (OWAD) induced OWAD (IOWAD). We present as with (BBAOWAD) IOWAD (BBAIOWAD). main advantage this approach that we can obtain m...

Xu and Da [Z.S. Xu, Q.L. Da, The uncertain OWA operator, International Journal of Intelligent Systems, 17 (2002) 569–575] introduced the uncertain ordered weighted averaging (UOWA) operator to aggregate the input arguments taking the form of intervals rather than exact numbers. In this paper, we develop some dependent uncertain ordered weighted aggregation operators, including dependent uncerta...

In the context of multiple attribute decision making, we present an aggregation scheme based on generalized mixture operators using weighting functions and we compare it with two standard aggregation methods: weighted averaging (WA) and ordered weighted averaging (OWA). Specifically, we consider linear and quadratic weight generating functions that penalize bad attribute performances and reward...

As a generalization of the L-fuzzy contexts, we propose the study of the L-fuzzy hypercontexts where the relation R between the objects X and the attributes Y takes as values other L-fuzzy relations. In this work, we propose the study of these structures using OWA operators in different situations. Finally, the practical case that has motivated this paper is analyzed.

For each single-parameter Gini social evaluation function, and by using the dual decomposition of the OWA operators, we derive two contributing factors. The …rst one, the self-dual core that can be considered as a positional measure, similar to the mean. The second one, the anti-self dual remainder, that we will prove is an equality measure with balanced sensitivity to both tails.

Andness directed aggregation is about selecting aggregators from a desired andness level. In this paper we consider operators of the OWA and WOWA families: functions that permit us to represent some degree compensation input values. addition compensation, permits importance (weights) Selection appropriate parameters given an level will be based on families fuzzy quantifiers.