2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery 2008
DOI: 10.1109/fskd.2008.293
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Application Interval-Valued Intuitionistic Fuzzy Set to Select Supplier

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Cited by 8 publications
(9 citation statements)
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“…In addition to the approach of aggregation operators, there are other techniques to handle MCDA problems based on IVIFSs, such as the linear programming model (Wang, Wang, & Li, 2008;Wang et al, 2009), grey relational analysis (Wei & Lan, 2008), TOPSIS (technique for order preference by similarity to the ideal solution) (Xiao & Wei, 2008), and the golden section ratio (Yue, Jia, & Zhu, 2008). However, there is little research on MCDA involving multiple decision-makers in an interval-valued intuitionistic fuzzy environment.…”
Section: Introductionmentioning
confidence: 98%
“…In addition to the approach of aggregation operators, there are other techniques to handle MCDA problems based on IVIFSs, such as the linear programming model (Wang, Wang, & Li, 2008;Wang et al, 2009), grey relational analysis (Wei & Lan, 2008), TOPSIS (technique for order preference by similarity to the ideal solution) (Xiao & Wei, 2008), and the golden section ratio (Yue, Jia, & Zhu, 2008). However, there is little research on MCDA involving multiple decision-makers in an interval-valued intuitionistic fuzzy environment.…”
Section: Introductionmentioning
confidence: 98%
“…The hesitancy function is found to be very useful in tackling multicriteria decision making problems [10][11][12]. More recently there has been some interest in applying IFS to handle the supplier selection problem [13][14][15].…”
Section: Introductionmentioning
confidence: 99%
“…In 2008, Wei, G., & Yi, W [14] proposed induced interval-valued intuitionistic fuzzy OWG operator. In 2008, Xiao, Z., & Wei, G [16] proposedapplication interval-valued intuitionistic fuzzy set to select a supplier. In 2009, Ye, J [19]presented multicriteria fuzzy decision-making method based on a novel accuracy function under interval-valued intuitionistic fuzzy environment.…”
Section: Introductionmentioning
confidence: 99%