MODIFICATION OF THE CRITIC METHOD USING FUZZY ROUGH NUMBERS

Abstract

This paper presents a new approach in the modification of the CRiteria Importance Through Intercriteria Correlation (CRITIC) method using fuzzy rough numbers. In the modified CRITIC method (CRITIC-M), the normalization procedure of the home matrix elements was improved and the aggregation function for information processing in the normalized home matrix was improved. By introducing a new way of normalization, smaller deviations between normalized elements are obtained, which affects smaller values of standard deviation. Thus, the relationships between the data in the initial decision matrix are presented in a more objective way. The introduction of a new way of aggregating the values of weights in the CRITIC-M method enables a more comprehensive view of information in the initial decision matrix, which leads to obtaining more objective values of weights. A new concept of fuzzy rough numbers was used to address uncertainties in the CRITIC-M methodology.