Comparing of modified distance-based Intuitionistic Fuzzy TOPSIS, VIKOR, and CODAS methods: An application to material selection for chest compression device

Distance-based Intuitionistic Fuzzy (IF) Multi-Criteria Decision-Making (MCDM) methods are mathematical approaches that effectively address complex decision-making processes. These methods aim to rank and select the most suitable alternatives by considering several conflicting criteria. In this study, a new IF selection metric suggested as an alternative to Euclidean and Taxicab distance functions, has been adapted to IF TOPSIS, IF VIKOR methods, and IF CODAS methods, which are distance-based MCDM methods. This comparative analysis has been effectively applied to an MCDM problem of ranking material alternatives of a chest compression device body to comprehensively evaluate the impact of this selection metric on different methods. The ranking results reveal that the new selection metric can be used in any distance-based MCDM method. The findings derived from the methods above indicate that the most suitable material for the chest compression device body is PC/ABS FR with a Flame Retardant (FR) feature created by blending Polycarbonate (PC) and Acrylonitrile Butadiene Styrene (ABS).