A novel q-rung orthopair fuzzy MAGDM method for healthcare waste treatment based on three-way decisions

In multi-attribute group decision-making (MAGDM) problems, q-rung orthopair fuzzy sets (q-ROFSs) can describe imprecise information more flexibly, and three-way decisions (TWDs) can deal with increasingly complex decision-making problems, and the integration of q-ROFSs and TWDs is the main trend of MAGDM research. In addition, cross entropy (CE), a common methodology in pattern recognition (PR), plays an important role in the information analysis process of MAGDM. In order to realize MAGDM under multigranulation q-rung orthopair fuzzy incomplete information system (MGq-ROFIIS), a new TWDs-based and CE-based MAGDM method is established. First, the concept of MGq-ROFIIS is given, and an information completion technique is proposed by considering missing scenarios. On this basis, the distance-based calculation method of expert weight and attribute weight with low computational overhead is given. Second, a new q-rung orthopair fuzzy Dombi probabilistic ordered weighted averaging (q-ROFDPOWA) operator is proposed, which considers both expert attitude and probability information, and realizes preference information fusion in different group environments. Third, for the aggregated MGq-ROFIIS, TWDs is used to divide three decision regions, CE is introduced as the ranking standard, and a new MAGDM method is constructed under both active and passive scenarios. Then, by applying the obtained results into healthcare waste treatment technologies (HCWTTs) selection, the feasibility and effectiveness of the method are illustrated, some suggestions for related departments in the aspects of technology selection and final decision-making are put forward, and the validity, stability and scientificity of the method are verified by reliability, sensitivity and comparative analyses. Finally, our method is applied to other classic MAGDM scenarios, which further proves the superior performance of the method.