Group decision-making analysis based on linguistic q-rung orthopair fuzzy generalized point weighted aggregation operators

The q-rung orthopair fuzzy sets (q-ROFSs), originally proposed by Yager, can express uncertain data to give decision-makers more space. The q-ROFS is a useful tool for describing imprecision, ambiguity, and inaccuracy, and the point operator is a useful aggregation operator which can manage the uncertainty and thus obtain intensive information within the decision-making process. In the latest realization, the linguistic q-rung orthopair fuzzy number (Lq-ROFN) is suggested where the linguistic variables are expressed as membership and non-membership of the Lq-ROFN. In this article, we propose the q-rung orthopair fuzzy linguistic family of point aggregation operators for linguistic q-rung orthopair fuzzy sets (Lq-ROFSs). Firstly, with the arithmetic and geometric operators, we introduce a new class of point-weighted aggregation operators to aggregate linguistic q-rung orthopair fuzzy information such as linguistic q-rung orthopair fuzzy point weighted averaging (Lq-ROFPWA) operators, linguistic q-rung orthopair fuzzy point weighted geometric (Lq-ROFPWG) operators, linguistic q-rung orthopair fuzzy generalized point weighted averaging (Lq-ROFGPWA) operators and linguistic q-rung orthopair fuzzy generalized point weighted geometric (Lq-ROFGPWG) operators. Then, we discuss some special cases and study the properties of these proposed operators. Based on Lq-ROFPWA and Lq-ROFPWG operators, a novel multi attribute group decision-making (MAGDM) methodology is designed to process the linguistic q-rung orthopair fuzzy information. Finally, we provide an example to demonstrate the applicability of the MAGDM. Consequently, the outstanding superiority of the developed methodology is assisted in a variety of ways by parameter exploration and thorough comparative analysis.