Selection of Knitted Fabrics Using a Hybrid BBWM-PFTOPSIS Method

Selecting the best knitted fabric with various comfort properties is considered a complicated multi-criteria decision-making (MCDM) issue that involves ambiguity and vagueness. In such scenarios, Pythagorean fuzzy sets (PFSs) provide an effective tool for addressing uncertainty in MCDM problems contain human subjective evaluations judgments. First, this research identifies factors affecting of fabrics as evaluation criteria. Second, Bayesian best-worst method (BBWM) preferred less pairwise comparisons obtains highly reliable results probabilistic perspective determining criteria weights. Furthermore, due to its logical computation approach ease operation, technique order preference by similarity ideal solution (TOPSIS) commonly utilized problems. Therefore, proposes innovative framework combines BBWM TOPSIS (PFTOPSIS). The determines weights, weighted sine similarity-based PFTOPSIS rank alternatives. proposed BBWM-PFTOPSIS was employed solve real-world case. Moreover, article conducts sensitivity analysis three comparative analyses reveal efficiency reliability approach. ranking establish viability effectiveness BBWM-PFTOPSIS.