Multiattribute decision making based on interval-valued intuitionistic fuzzy values |
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| Authors: | Shyi-Ming Chen Li-Wei Lee Hsiang-Chuan Liu Szu-Wei Yang |
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| Affiliation: | 1. Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC;2. Graduate Institute of Educational Measurement and Statistics, National Taichung University of Education, Taichung, Taiwan, ROC;3. Department of Computer and Communication Engineering, De Lin Institute of Technology, New Taipei City, Taiwan, ROC;4. Department of Biomedical Informatics, Asia University, Taichung, Taiwan, ROC;5. Department of Education, National Taichung University of Education, Taichung, Taiwan, ROC;1. College of Information Technology, Jiangxi University of Finance and Economics, Nanchang, 330013, China;2. College of Statistics, Jiangxi University of Finance and Economics, Nanchang, 330013, China;1. School of Mathematical Sciences, Anhui University, Hefei, Anhui 230601, China;2. School of Business, Anhui University, Hefei, Anhui 230601, China |
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| Abstract: | In this paper, we present a new multiattribute decision making method based on the proposed interval-valued intuitionistic fuzzy weighted average operator and the proposed fuzzy ranking method for intuitionistic fuzzy values. First, we briefly review the concepts of interval-valued intuitionistic fuzzy sets and the Karnik–Mendel algorithms. Then, we propose the intuitionistic fuzzy weighted average operator and interval-valued intuitionistic fuzzy weighted average operator, based on the traditional weighted average method and the Karnik–Mendel algorithms. Then, we propose a fuzzy ranking method for intuitionistic fuzzy values based on likelihood-based comparison relations between intervals. Finally, we present a new multiattribute decision making method based on the proposed interval-valued intuitionistic fuzzy weighted average operator and the proposed fuzzy ranking method for intuitionistic fuzzy values. The proposed method provides us with a useful way for multiattribute decision making based on interval-valued intuitionistic fuzzy values. |
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