Elsevier

Fuzzy Sets and Systems

Volume 136, Issue 2, 1 June 2003, Pages 203-215
Fuzzy Sets and Systems

On obtaining minimal variability OWA operator weights

https://doi.org/10.1016/S0165-0114(02)00267-1Get rights and content

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.

References (10)

There are more references available in the full text version of this article.

Cited by (263)

  • Wasserstein distance for OWA operators

    2024, Fuzzy Sets and Systems
  • The median under orness

    2024, Fuzzy Sets and Systems
View all citing articles on Scopus

Partially supported by the Hungarian Research Funds OTKA T32412 and FKFP-0157/2000.

View full text