Abstract
Actual result of aggregation performed by an ordered weighted averaging (OWA) operator heavily depends upon the weighting vector used. A number of approaches for obtaining the associated weights have been suggested in the academic literature. In this paper, we present a method for determining the OWA weights when (1) the preferences of some subset of alternatives over other subset of alternatives are specified in a holistic manner across all the criteria, and (2) the consequences (criteria values) are specified in one of three different formats: precise numerical values, intervals and fuzzy numbers. The OWA weights are to be estimated in the direction of minimizing deviations from the OWA weights implied by the preference relations, thus as consistent as possible with a priori preference relations.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
