Decision making is the process of finding the best option among the feasible alternatives. In classical multiple criteria decision making (MCDM) methods, the ratings and the weights of the criteria are known precisely. Owning to vagueness of the decision data, the crisp data are inadequate for real-life situations. Since human judgments including preferences are often vague and cannot be expressed by exact numerical values, the application of fuzzy concepts in decision making is deemed to be relevant. Here, we apply a new distance formula to compute the standard deviation of fuzzy data to achieve crisp data by normalization. There is a flexibility to consider various fuzzy values as triangular, trapezoidal, interval, etc. Finally, we use the TOPSIS to determine the ranking order of the alternatives. Two numerical examples from the literature are solved to demonstrate applicability of the proposed model.

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