Aggregation methods for fuzzy judgments
Ayesha Syed. Lahore School of Economics, Lahore 53200, Pakistan.
Ismat Beg. Lahore School of Economics, Lahore 53200, Pakistan.
Asma Khalid. Lahore School of Economics, Lahore 53200, Pakistan.
- Fuzzy Economic Review: Volume 21, Number 1, 2016
- DOI: 10.25102/fer.2016.01.01
Abstract
Arrow (1963) established that a group cannot always reach logically consistent collective outcome. Subsequently many developments like premise based, conclusion based and distance based methods have emerged in literature to reach group consistency. This study is focused on the judgment aggregation in fuzzy logic based setting with novel involvement of family of t-norms. We compare three distance based methods due to Miller and Osherson (2009) using Łukasiewicz and min t-norm. These methods in fuzzy logic based settings give closer results to consistency of outcome. It also broaden the set of properties and authenticity of the methods. Distance methods in our study also satisfy Arrow’s axioms in solution method.