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Soft Computing
Erschienen in: Soft Computing 8/2014

01.08.2014 | Methodologies and Application

Consistency test and weight generation for additive interval fuzzy preference relations

verfasst von: Yejun Xu, Kevin W. Li, Huimin Wang

Erschienen in: Soft Computing | Ausgabe 8/2014

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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).
Vorheriger Artikel Prediction in evolutionary algorithms for dynamic environments
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Metadaten
Titel
Consistency test and weight generation for additive interval fuzzy preference relations
verfasst von
Yejun Xu
Kevin W. Li
Huimin Wang
Publikationsdatum
01.08.2014
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 8/2014
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-013-1156-x

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