Application of Extended Fuzzy ISOCOV Methodology in Nanomaterial Selection Based on Performance Measures
Nivetha Martin, Seyyed Ahmad Edalatpanah
Abstract
The prevalence of decision-making methodologies catering to quantitative attributes considerably overshadows those designed for qualitative attributes. This study seeks to address this gap by extending the traditional Ideal Solutions with Constraint on Values (ISOCOV) method to a fuzzy environment, thereby enhancing its capability to handle optimal decision-making based on qualitative attributes. In this improved method, $\alpha$-cut representations are employed for managing linguistic value constraints in performance-oriented data. The proposed approach is then utilized for the selection of nanomaterials, evaluated based on five essential criteria. By subjecting the performance-based decision matrix to the modified fuzzy method, a ranking of alternatives is derived. Compared to its traditional counterpart, this fuzzy-enhanced ISOCOV method demonstrates enhanced efficiency in processing qualitative data, promising its potential compatibility and utility for decision makers dealing with performance-oriented decision-making.