The Maclaurin symmetric mean (MSM) and dual Maclaurin symmetric mean (DMSM)
operators are two aggregation operators to aggregate the q-rung orthopair fuzzy numbers (q …

The Maclaurin symmetric mean (MSM) operator is a classical mean type aggregation
operator used in modern information fusion theory, which is suitable to aggregate numerical …

In the article, we establish two multiple attribute decision making (MADM) approaches using
the developed weighted generalized Maclaurin symmetric mean (q-ROFWGMSM) and …

In respect to the multi-attribute group decision making (MAGDM) problems in which the
evaluated value of each attribute is in the form of q-rung orthopair fuzzy numbers (q-ROFNs) …

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 …

The q‐rung orthopair set (q‐ROFSs) can serve as a generalization of the existing orthopair
fuzzy sets, including intuitionistic fuzzy sets and Pythagorean fuzzy sets. The most desirable …

To be able to describe more complex fuzzy uncertainty information effectively, the concept of
q-rung orthopair fuzzy sets (q-ROFSs) was first proposed by Yager. The q-ROFSs can …

The Maclaurin symmetric mean (MSM) operator is a classical mean type aggregation
operator used in modern information fusion theory, which is suitable to aggregate numerical …

The generalized Heronian mean and geometric Heronian mean operators provide two
aggregation operators that consider the interdependent phenomena among the aggregated …

Recently proposed q-rung orthopair fuzzy set (q-ROFS) is a powerful and effective tool to
describe fuzziness, uncertainty and vagueness. The prominent feature of q-ROFS is that the …