An augmented fuzzy decision support system to analyse compatible cosmetic face masks for various complexions

Abstract

Beauty face masks (BFM) are becoming increasingly popular among both men and women since they provide quick refreshment and nurture the skin. Given the wide range of skin types and the chemicals used in their formulation, it can be difficult to find a product that not only complements the skin type but is also free of potentially harmful ingredients that could endanger the consumer's health. When dealing with ambiguous situations, the multi-attribute decision making (MADM) approach combined with fuzzy set theory is more effective. Type-2 fuzzy sets (T2FS) provide greater flexibility in dealing with uncertainty in real-world issues since they are characterised by a main and secondary membership function. In this research, we present the innovative idea of type-2 linear diophantine fuzzy set (T2LDFS) as an intriguing tool for capturing expert reluctance about an issue. For analysing the discussed problem, a hybrid fuzzy VIKOR enhanced with the proposed fuzzy logic is suggested. A sensitivity and comparative analysis is carried out to establish the validity of the recommended approach.