mean aggregation operators, fuzzy aggregations, fuzzy measure, fuzzy numbers, fuzzy decision making.
The Ordered Weighted Averaging (OWA) operator was introduced by R.R. Yager  to provide a method for aggregating inputs that lie between the max and min operators. In this article we continue to present some extensions of OWA-type aggregation operators. Several variants of the generalizations of the fuzzy-probabilistic OWA operator - FPOWA (introduced by J.M. Merigo [13,14]) are presented in the environment of fuzzy uncertainty, where different monotone measures (fuzzy measure) are used as uncertainty measures. The considered monotone measures are: possibility measure, Sugeno −λadditive measure, monotone measure associated with Belief Structure and Choquet capacity of order two. New aggregation operators are introduced: AsFPOWA and SA-AsFPOWA. Some properties of new aggregation operators and their information measures are proved. Concrete faces of new operators are presented with respect to different monotone measures and mean operators. Concrete operators are induced by the Monotone Expectation (Choquet integral) or Fuzzy Expected Value (Sugeno integral) and the Associated Probability Class (APC) of a monotone measure. New aggregation operators belong to the Information Structure I6 (see Part I, section 3). For the illustration of new constructions of AsFPOWA and SA-AsFPOWA operators an example of a fuzzy decision making problem regarding the political management with possibility uncertainty is considered. Several aggregation operators (“classic” and new operators) are used for the comparing of the results of decision making.
Cite this paper
Gia Sirbiladze, Otar Badagadze, Gvantsa Tsulaia. (2016) New Fuzzy Aggregations. Part III: Application of New FPOWA Operators in the Problem of Political Management. International Journal of Control Systems and Robotics, 1, 86-95