This paper is an attempt to solve various problems by the two factors of mean and standard deviation (SD) of variables, introducing coefficient of variation (CV) of data as the best option for prioritization, scaling, pairwise comparison and normalization of quantitative and qualitative variables. An algorithm was built based on a coefficient of variation scales triangle (CVST) consisting of natural numbers with coefficients of binomial expansion for each line, followed by new and independent grading and scaling. In view of the existing factors, the theory provides higher generalization and maximum reliability rates in comparison to other methods for multiple-criteria decision analysis (MCDA). On the other hand, in the normalization process of different variables (i.e. de-scalarization), a precise and infinite model was presented based on coefficient of variation scale triangle (multipurpose triangle), in such a way that decision makers could work with the software in a more convenient and precise manner. Therefore, the proposed theories may be considered as a new approach and definition in the valuation and progress of MCDA.
theories; coefficient of variation scales triangle (CVST); multiple-criteria decision analysis (MCDA), theories, coefficient of variation scales triangle (CVST), multiple criteria decision analysis (MCDA)
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