EconPapers    
Economics at your fingertips  
 

AGGREGATION METHODS FOR FUZZY JUDGMENTS

A. Syed, Ismat Beg and A. Khalid
Additional contact information
A. Syed: Lahore School of Economics, Lahore 53200, Pakistan
A. Khalid: Lahore School of Economics, Lahore 53200, Pakistan

Fuzzy Economic Review, 2016, vol. 21, issue 1, 3-21

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 Lukasiewicz 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.

Keywords: judgment aggregation; fuzzy; collective decision (search for similar items in EconPapers)
JEL-codes: C02 C60 D71 (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (1)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:fzy:fuzeco:v:21:y:2016:i:1:p:3-21

Access Statistics for this article

More articles in Fuzzy Economic Review from International Association for Fuzzy-set Management and Economy (SIGEF) Contact information at EDIRC.
Bibliographic data for series maintained by Aurelio Fernandez ( this e-mail address is bad, please contact ).

 
Page updated 2025-03-19
Handle: RePEc:fzy:fuzeco:v:21:y:2016:i:1:p:3-21