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Multicriteria fuzzy decision-making method based on weighted correlation coefficients under interval-valued intuitionistic fuzzy environment
To identify the best alternative in multicriteria decision-making problems, a multicriteria fuzzy decision-making method based on the weighted correlation coefficient of interval-valued intuitionistic fuzzy sets (IVIFSs) is established in which criterion values for alternatives are IVIFSs and the criterion weights are known information. With the definition of ideal and anti-ideal weighted correlation coefficients, an objective function is constructed to derive the optimal evaluation for the weight of each alternative. The ranking of alternatives and the best one can be determined directly on the basis of the weights of alternatives. The evaluation process is simple and easy to use in practice. Finally, an illustrative example demonstrates the practicality and effectiveness of the proposed method.
Multicriteria fuzzy decision-making method based on weighted correlation coefficients under interval-valued intuitionistic fuzzy environment
To identify the best alternative in multicriteria decision-making problems, a multicriteria fuzzy decision-making method based on the weighted correlation coefficient of interval-valued intuitionistic fuzzy sets (IVIFSs) is established in which criterion values for alternatives are IVIFSs and the criterion weights are known information. With the definition of ideal and anti-ideal weighted correlation coefficients, an objective function is constructed to derive the optimal evaluation for the weight of each alternative. The ranking of alternatives and the best one can be determined directly on the basis of the weights of alternatives. The evaluation process is simple and easy to use in practice. Finally, an illustrative example demonstrates the practicality and effectiveness of the proposed method.
Multicriteria fuzzy decision-making method based on weighted correlation coefficients under interval-valued intuitionistic fuzzy environment
Luo Yongbiao, (author) / Jun, Ye (author) / Ma Xiaowen, (author)
2009-11-01
74014 byte
Conference paper
Electronic Resource
English
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