In this work, a new ranking approach of triangular intuitionistic fuzzy numbers (TIFNs) is proposed and applied to solve multi-attribute decision making (MADM) problems. Firstly, I use a weighted average operator to introduce the risk preference of the decision maker (DM), and construct the score and accuracy expected functions of TIFN. Then, based on these concepts, a ranking method for TIFNs is developed considering the DM’s risk preference. Subsequently, a decision procedure is described to deal with the MADM under a triangular intuitionistic fuzzy environment. Moreover, a novel distance measure for TIFNs is defined and utilized to determine the attribute weights. Finally, a trusted cloud service selection example verifies the effectiveness and practicality of the developed method.
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