A method based on preference degrees for handling hybrid multiple attribute decision making problems |
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| Authors: | Xiaohan Yu Zeshui Xu Qi Chen |
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| Affiliation: | 1. Kansas State University, Manhattan, Kansas, USA;2. International Institute of Information Technology, Bangalore, India;1. School of Materials Science and Engineering, Shanghai University, Shanghai 200444, PR China;2. Jiangsu Key Laboratory of Micro and Nano Heat Fluid Flow Technology and Energy Application & Research Center for Solid State Physics and Materials, S, Suzhou University of Science and Technology, Suzhou, Jiangsu 215009, PR China;3. Shanghai Institute of Ceramics, Chinese Academy of Sciences, Shanghai 200050, PR China |
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| Abstract: | In this paper, we investigate hybrid multiple attribute decision making problems with various forms of attribute values (real numbers, linguistic labels, interval numbers, intuitionistic fuzzy numbers and interval intuitionistic fuzzy numbers). We propose a method based on preference degrees which may take the forms of fuzzy numbers, intuitionistic fuzzy numbers and interval intuitionistic fuzzy numbers. The method first normalizes various forms of attribute values into preference degrees, and then uses a preference degree-based weighted averaging operator to aggregate the normalized preference degrees. Meanwhile, for convenience of calculation, a new linguistic representation model is presented, whose feasibility is verified by comparing it with the traditional 4-tuple linguistic representation model, and from our model, the mapping relationship between interval intuitionistic fuzzy numbers and linguistic labels can be constructed. Finally, we illustrate the rationality and practicality of the proposed method by an application example. |
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