Abstract
Hair masks (HMs) act as one of the solutions for most of the hair problems like dandruff, frizziness, breakage, premature- greying and so on. Due to its various benefits, HM products are acquiring more popularity among the individuals. As there are different varieties of HM products available in the market, the confusion arises in choosing a HM which suits the individual’s hair profile and causes less side effects. Here, we have employed multi-criteria decision-making (MCDM) combined with fuzzy set theory to obtain better results. We used the extended Weighted Aggregated Sum Product Assessment (WASPAS) method based on trapezoidal interval type-2 fuzzy set (TIT2FS) in this research paper to handle vagueness and complexity in real-world problems. For determining the objective weights of the criteria, we used the entropy method of weight finding. An example of selecting a hair mask product (HMP) among four alternatives based on five criteria is provided to illustrate the applicability of the proposed method. In comparison to other MCDM methods, the approach yielded more practical results. By doing a sensitive study, the method’s stability is also assessed.
Highlights
Hair is one of the best natural gifts that everyone has
As it acts as one of the solutions for different hair problems, trapezoidal interval type-2 fuzzy set (TIT2FS)-based Weighted Aggregated Sum Product Assessment (WASPAS) method is used in choosing a suitable hair mask product which suits different hair profile and causes minimal side effects as it provides more realistic results in handling multi-criteria decision-making (MCDM) problems
The MCDM method namely WASPAS method, which is the aggregation of two methods namely Weighted Product Model (WPM) and Weighted Sum Model (WSM), is employed in this study to provide more accuracy in decision-making process when compared to the individual methods
Summary
Hair is one of the best natural gifts that everyone has. It is important to make the hair look beautiful and presentable. Mehdi Keshavarz-Ghorabaee et al [18] have proposed an interval type-2 fuzzy MCDM method based on WASPAS and CRITIC for evaluating and selecting an appropriate third-party logistic provider. A hybrid method involving Best Worst Method (BWM), WASPAS and TOPSIS have been developed based on the intutionistic fuzzy environment for resilient green supplier selection problem by Lei Xiong et al [21]. Mehdi Keshavarz Ghorabaee et al [24] have employed IT2FS-based extended WASPAS method for green supplier selection problem. Nowadays hair mask products are used by different age groups for nourishing and maintaining the texture of the hair As it acts as one of the solutions for different hair problems, TIT2FS-based WASPAS method is used in choosing a suitable hair mask product which suits different hair profile and causes minimal side effects as it provides more realistic results in handling MCDM problems. TIT2FS are involved as they are more flexible in handling uncertain data when compared to T1FS
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