On obtaining minimal variability OWA operator weights

Robert Fullér, Péter Majlender

Research output: Contribution to journalArticle

222 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)203-215
Number of pages13
JournalFuzzy Sets and Systems
Issue number2
Publication statusPublished - Jun 1 2003


  • Fuzzy sets
  • Lagrange multiplier
  • Multiple criteria analysis
  • OWA operator

ASJC Scopus subject areas

  • Logic
  • Artificial Intelligence

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