INTUITIONISTIC FUZZY DIMENSIONAL ANALYSIS FOR MULTI-CRITERIA DECISION MAKING

Abstract

Dimensional analysis, for multi-criteria decision making, is a mathematical method that includes diverse heterogeneous criteria into a single dimensionless index. Dimensional Analysis, in its current definition, presents the drawback to manipulate fuzzy information commonly presented in a multi-criteria decision making problem. To overcome such limitation, we propose two dimensional analysis based techniques under intuitionistic fuzzy environments. By the arithmetic operations of intuitionistic fuzzy numbers, we describe the intuitionistic fuzzy dimensional analysis (IFDA) and the aggregated intuitionistic fuzzy dimensional (AIFDA) techniques. In the first technique, we consider only the handling of fuzzy information; and, in the second one we consider both quantitative (crisp) and qualitative (fuzzy) information typically presented together in a decision making problem. To illustrate our approaches, we present some numerical examples and perform some comparisons with other well-known techniques.