| Summary: | 博士 === 國立臺灣科技大學 === 資訊工程系 === 105 === Many multiple attribute decision making problems in the real-world become more uncertain and more complex. In recent years, multiple attribute decision making based on interval type-2 fuzzy sets and interval-valued intuitionistic fuzzy sets become important research topics. In this dissertation, we propose three new multiple attribute decision making methods based on interval type-2 fuzzy sets and interval-valued intuitionistic fuzzy sets, respectively, where (1) we propose a new multiple attribute decision making method based on ranking interval type-2 fuzzy sets and the -cuts of interval type-2 fuzzy sets, (2) we propose a new multiple attribute decision making method based on interval-valued intuitionistic fuzzy sets, the linear programming methodology and the extended technique for order preference by similarity to ideal solution (TOPSIS) method, where the ratings of the attributes of alternatives and the weights of attributes are represented by interval-valued intuitionistic fuzzy values and the linear programming methodology is used to obtain optimal weights of attributes, and (3) we propose an improved multiple attribute decision making method based on the proposed new score function of interval-valued intuitionistic fuzzy sets and the linear programming methodology. The experimental results show that the proposed multiple attribute decision making methods can overcome the drawbacks of the existing methods, where the existing methods have the drawbacks that they get unreasonable preference orders of the alternatives in some situations and they cannot get the preference order of the alternatives in some situations. The proposed methods provide us with a very useful way for multiple attribute decision making in interval type-2 fuzzy environments and interval-valued intuitionistic fuzzy environments, respectively.
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