New q‐rung orthopair fuzzy partitioned Bonferroni mean operators and their application in multiple attribute decision making

The q‐rung orthopair fuzzy sets are superior to intuitionistic fuzzy sets or Pythagorean fuzzy sets in expressing fuzzy and uncertain information. In this paper, some partitioned Bonferroni means (BMs) for q‐rung orthopair fuzzy values have been developed. First, the q‐rung orthopair fuzzy partitioned BM (q‐ROFPBM) operator and the q‐rung orthopair fuzzy partitioned geometric BM (q‐ROFPGBM) operator are developed. Some desirable properties and some special cases of the new aggregation operators have been studied. The q‐rung orthopair fuzzy weighted partitioned BM (q‐ROFWPBM) operator and the q‐rung orthopair fuzzy partitioned geometric weighted BM (q‐ROFPGWBM) operator are also developed. Then, a new multiple‐attribute decision‐making method based on the q‐ROFWPBM (q‐ROFPGWBM) operator is proposed. Finally, a numerical example of investment company selection problem is given to illustrate feasibility and practical advantages of the new method.