Abstract
To cope with the uncertainty in the process of decision making, fuzzy preference relations are proposed and commonly applied in many fields. In practical decision-making problems, the decision maker may use triangular fuzzy preference relations to express his/her uncertainty. Based on the row weighted arithmetic mean method, this paper develops an approach for deriving the fuzzy priority vector from triangular fuzzy compare wise judgment matrices. To do this, this paper first analyzes the upper and lower bounds of the triangular fuzzy priority weight of each alternative, which indicates the decision maker’s optimistic and pessimistic attitudes. Based on (acceptably) consistent multiplicative preference relations, the triangular fuzzy priority vector is obtained. Meanwhile, a consistency concept of triangular fuzzy compare wise judgment matrices is defined, and the consistent relationship between triangular fuzzy and crisp preference relations is studied. Different to the existing methods, the new approach calculates the triangular fuzzy priority weights separately. Furthermore, the fuzzy priority vector from trapezoidal fuzzy reciprocal preference relations is considered. Finally, the application of the new method to new product development (NDP) project screening is tested, and comparative analyses are also offered.







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Acknowledgments
The authors first gratefully thank the Area Editor and three anonymous referees for their valuable and constructive comments which have much improved the paper. This work was supported by the State Key Program of National Natural Science of China (No. 71431006), the National Natural Science Foundation of China (Nos. 71571192, 71501189), the China Postdoctoral Science special Foundation (2015T80901), the China Postdoctoral Science Foundation (2014M560655), and the Innovation-Driven Planning Foundation of Central South University (2015CX010).
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Meng, F., Chen, X. A New Method for Triangular Fuzzy Compare Wise Judgment Matrix Process Based on Consistency Analysis. Int. J. Fuzzy Syst. 19, 27–46 (2017). https://doi.org/10.1007/s40815-016-0150-8
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DOI: https://doi.org/10.1007/s40815-016-0150-8