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On Obtaining Minimal Variability OWA Operator Weights

Robert Fullér, Péter Majlender, On Obtaining Minimal Variability OWA Operator Weights. Fuzzy Sets and Systems 136, 203–215, 2003.

Abstract:

One important issue in the theory of
Ordered Weighted Averaging (OWA)
operators is the determination of the associated weights.
One of the first approaches, suggested by O'Hagan,
determines a special class of OWA
operators having maximal entropy of the
OWA weights for a given level of {\em orness};
algorithmically it is based on
the solution of a constrained optimization
problem.
Another consideration that may be of
interest to a decision maker involves
the variability associated
with a weighting vector. In particular, a decision maker
may desire low variability
associated with a chosen weighting vector.
In this paper, using the Kuhn-Tucker
second-order sufficiency conditions
for optimality, we shall analytically
derive the minimal variablity
weighting vector for any level of {\em orness}.

BibTeX entry:

@ARTICLE{jFuMa03a,
  title = {On Obtaining Minimal Variability OWA Operator Weights},
  author = {Fullér, Robert and Majlender, Péter},
  journal = {Fuzzy Sets and Systems},
  volume = {136},
  pages = {203–215},
  year = {2003},
}

Belongs to TUCS Research Unit(s): Other

Publication Forum rating of this publication: level 1

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