Algorithms to Detect and Rectify Multiplicative and Ordinal Inconsistencies of Fuzzy Preference Relations

Date

2019-07

Advisors

Journal Title

Journal ISSN

ISSN

Volume Title

Publisher

IEEEXplore

Type

Article

Peer reviewed

Yes

Abstract

Consistency, multiplicative and ordinal, of fuzzy preference relations (FPRs) is investigated. The geometric consistency index (GCI) approximated thresholds are extended to measure the degree of consistency for an FPR. For inconsistent FPRs, two algorithms are devised (1) to find the multiplicative inconsistent elements, and (2) to detect the ordinal inconsistent elements. An integrated algorithm is proposed to improve simultaneously the ordinal and multiplicative consistencies. Some examples, comparative analysis, and simulation experiments are provided to demonstrate the effectiveness of the proposed methods.

Description

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.

Keywords

Citation

Xu, J., Li, M., Cabrerizo, F.J., Chiclana, F. and Herrera-Viedma, E. (2019) Algorithms to Detect and Rectify Multiplicative and Ordinal Inconsistencies of Fuzzy Preference Relations. IEEE Transactions on Systems, Man and Cybernetics: Systems.

Rights

Research Institute

Institute of Artificial Intelligence (IAI)