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In this thesis, we propose a new multiattribute decision making method based on probability density functions and the variances and standard deviations of the largest ranges of evaluating interval-valued intuitionistic fuzzy values. First, the proposed method obtains the largest range of each evaluating interval-valued intuitionistic fuzzy value in the decision matrix provided by the decision maker. Then, it computes the average value of the largest ranges of each attribute. Then, it obtains the probability density function of the largest range of each evaluating interval-valued intuitionistic fuzzy value appearing in the decision matrix. Then, it computes the variance of each largest range and calculates the standard deviation of the largest ranges of each attribute. Then, it builds the z-score decision matrix based on the obtained largest range of each evaluating interval-valued intuitionistic fuzzy value appearing in the decision matrix, the obtained average value of the largest ranges of each attribute and the obtained standard deviation of the largest ranges of each attribute. Then, it gets the transformed weight of the interval-valued intuitionistic fuzzy weight of each attribute. Finally, it computes the weighted score of each alternative based on the obtained z-score decision matrix and the transformed weight of the interval-valued intuitionistic fuzzy weight of each attribute. The larger the value of the weighted score, the better the preference order of the alternative. The proposed multiattribute decision making method can conquer the shortcomings of the existing multiattribute decision making methods. It provides us with a very useful way for multiattribute decision making in interval-valued intuitionistic fuzzy environments.
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