Elsevier

Fuzzy Sets and Systems

Volume 216, 1 April 2013, Pages 108-133
Fuzzy Sets and Systems

Algorithms for improving consistency or consensus of reciprocal [0,1]-valued preference relations

https://doi.org/10.1016/j.fss.2012.09.016Get rights and content

Abstract

We investigate the consistency and consensus of reciprocal [0,1]-valued preference relations (also called fuzzy preference relations by many authors) based on the multiplicative consistency property, which is an important issue in fuzzy set theory. An algorithm is first developed to improve the consistency level of a reciprocal [0,1]-valued preference relation, and the corresponding algorithm for the incomplete reciprocal [0,1]-valued preference relation is also developed. We further propose the consensus improving algorithms for individual reciprocal [0,1]-valued preference relations or incomplete ones. The convergence and robustness of the algorithms are proven and some important conclusions are obtained. In addition, the proposed algorithms can improve the consistency or consensus of reciprocal [0,1]-valued preference relations with less interactions with the decision makers, which can save a lot of time and obtain the results quickly.

References (40)

Cited by (98)

View all citing articles on Scopus

The work was supported in part by the National Natural Science Foundation of China (Nos. 71071161 and 61273209) and the China Postdoctoral Science Foundation (No. 2012M520311).

View full text