On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Fuzzy Sets and Systems
Analytic properties of maximum entropy OWA operators
Information Sciences—Informatics and Computer Science: An International Journal
On the issue of obtaining OWA operator weights
Fuzzy Sets and Systems
Nearest-neighbor guided evaluation of data reliability and its applications
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On characterizing features of OWA aggregation operators
Fuzzy Optimization and Decision Making
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An important issue when using the OWA aggregation operators is the determination of weights. One approach is to link the weights to a desired attitudinal character for the aggregation. The ME-OWA operators provide a pioneering example of this approach. Here we first present an alternative approach to generating OWA weights with a desired attitudinal character. We accomplish this by using a family of recursive OWA operators (R-OWA). We then generalize this with a class that allows of OWA aggregation by iteration (It-OWA). Both families are built with the constraint of keeping constant the attitudinal character at any recursion or any iteration step. This is particularly useful in aggregations that sequentially add arguments to the aggregation.