On obtaining minimal variability OWA operator weights

  • Authors:
  • Robert Fullér;Péter Majlender

  • Affiliations:
  • Department of Operations Research, Eötvös Loránd University, Budapest, Hungary and IAMSR, Åbo Akademi University, Lemminkäinengatan 14B, FIN-20520 Åbo, Finland;TUCS, Turku Centre for Computer Science and IAMSR, Åbo Akademi University, Lemminkäinengatan 14B, Finland and Department of Operations Research, Eötvös Loránd University, ...

  • Venue:
  • Fuzzy Sets and Systems - Theme: Multicriteria decision
  • Year:
  • 2003

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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 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 variability weighting vector for any level of orness.