Multiple-Attribute Decision-Making Based on Archimedean Bonferroni Operators of q-Rung Orthopair Fuzzy Numbers

The theory of q-rung orthopair fuzzy sets (q-ROFSs) proposed by Yager effectively describes fuzzy information in the real world. Because q-ROFSs contain the parameter q and can adjust the range of expressed fuzzy information, they are superior to both intuitionistic and Pythagorean fuzzy sets. Archimedean T-norm and T-conorm (ATT) is an important tool used to generate operational rules based on the q-rung orthopair fuzzy numbers (qROFNs). In comparison, the Bonferroni mean (BM) operator has an advantage because it considers the interrelationships between the different attributes. Therefore, it is an important and meaningful innovation to extend the BM operator to the q-ROFNs based upon the ATT. In this paper, we first discuss q-rung orthopair fuzzy operational rules by using ATT. Furthermore, we extend BM operator to the q-ROFNs and propose the q-rung orthopair fuzzy Archimedean BM (q-ROFABM) operator and the q-rung orthopair fuzzy weighted Archimedean BM (q-ROFWABM) operator and study their desirable properties. Then, a new multiple attribute decision-making (MADM) method is developed based on q-ROFWABM operator. Finally, we use a practical example to verify effectiveness and superiority by comparing to other existing methods.