An extended CoCoSo method under (p–q) rung orthopair fuzzy environment for multi-criteria decision-making applications

The management of health care waste (HCW) is a major environmental and public health challenge, especially in developing nations. A complex multi-criteria decision analysis problem encompassing both qualitative and quantitative aspects is the choice of the best technology for HCW disposal. It is possible to evaluate HCW treatment technologies using ambiguous or inaccurate data. Furthermore, the majority of current HCW decision models are unable to account for these intricate interactions. The (p-q) rung orthopair fuzzy set is integrated in this research to present a novel hybrid multi-criteria decision making (MCDM) model. Due to the greater range of their membership grades, (p-q) rung orthopair fuzzy sets can offer more ambiguous scenarios than Fermatean, Pythagorean, and intuitionistic fuzzy sets. We first develop basic operational criteria to characterize some aggregation operators (AOs) under Sugeno-Weber operations, comprising the Sugeno-Weber weighted averaging operator for (p-q) rung orthopairs ((p-q) ROFSWWA). We investigate these operators' basic characteristics in further detail. To determine the ranking of alternatives, an enhanced combination compromise solution approach is suggested in this study. We provide a case study on HCW management selection to demonstrate the usefulness of our suggested approach. Comparing our suggested decision-making procedure to current MCDM techniques demonstrates its high efficacy and dependability in evaluating and rating HCW.