Document Type
Article
Publication Date
8-2014
Publication Title
Soft Computing
Volume
18
Issue
8
First Page
1499
Keywords
Multiple criteria decision analysis, Interval fuzzy preference relation, Consistency test, Weight generation, Additive consistent, Linear programming
Last Page
1513
Abstract
Some simple yet pragmatic methods of consistency test are developed to check whether an interval fuzzy preference relation is consistent. Based on the definition of additive consistent fuzzy preference relations proposed by Tanino (Fuzzy Sets Syst 12:117–131, 1984), a study is carried out to examine the correspondence between the element and weight vector of a fuzzy preference relation. Then, a revised approach is proposed to obtain priority weights from a fuzzy preference relation. A revised definition is put forward for additive consistent interval fuzzy preference relations. Subsequently, linear programming models are established to generate interval priority weights for additive interval fuzzy preference relations. A practical procedure is proposed to solve group decision problems with additive interval fuzzy preference relations. Theoretic analysis and numerical examples demonstrate that the proposed methods are more accurate than those in Xu and Chen (Eur J Oper Res 184:266–280, 2008b).
DOI
10.1007/s00500-013-1156-x
Recommended Citation
Xu, Yejun; Li, Kevin; and Wang, Huimin. (2014). Consistency test and weight generation for additive interval fuzzy preference relations. Soft Computing, 18 (8), 1499-1513.
https://scholar.uwindsor.ca/odettepub/91
Comments
The final publication is available at Springer via http://dx.doi.org/10.1007/s00500-013-1156-x