Enhanced CRITIC-REGIME method for decision making based on Pythagorean fuzzy rough number

Rough set theory has revolutionized data analysis by exploring and extracting valuable insights from imprecise data. The concept of Pythagorean fuzzy sets is a relatively novel mathematical framework in the fuzzy family with a higher ability to deal with imprecision embedded in decision making. Both theories can be combined to develop a broader Pythagorean fuzzy rough numbers for maximum benefit. The CRiteria Importance Through Intercriteria Correlation (CRITIC) and REGIME methods have appeared as successful methods for estimating the weights of criteria and ranking alternatives, respectively, in the field of multi-criteria decision-making (MCDM). In this study, our main objective is to develop a new methodology based on Pythagorean fuzzy rough numbers by integrating CRITIC and REGIME methodologies for the first time. The proposed Pythagorean fuzzy rough CRITIC-REGIME methodology (PFR-CRITIC-REGIME) is implemented to solve the sustainable supply chain problem of an electric ferry in public transit. The proposed method is thoroughly compared with some other existing decision making methods. The results of these evaluations are shown very reliable results. A sensitivity analysis is also performed.