On the Minimax Disparity Obtaining OWA Operator Weights

서지정보

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· 저자명 : 홍덕헌

초록

The determination of the associated weights in the theory of ordered weighted averaging (OWA)operators is one o fthe important issue. Recently, Wang and Parkan [Information Sciences 175 (2005) 20-29]proposed a minimax disparity approach for obtaining OWA operator weights and the approach is based on the solution of aline arprogram (LP) model for a given degree of orness. Recently, Liu[International Journal of Approximate Reasoning, accepted] showed that
the minimum variance OWA problem of Full´er and Majlender [Fuzzy Sets and Systems 13 (2003) 203-215]and the minimax disparity OWA problem of Wang and Park analways produce the same weight vector using the dual theory of linear programming. In this paper, we give an improved proof of the minimax disparity problem of Wang and Parkan while Liu’s method is rather complicated. Our method gives the exact optimum solution of OWA operator weights for all
levels of orness, 0 ≤ α ≤ 1, whos evalues are piecewise linear and continuous functions of α.

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