Selection of Appropriate Global Partner for Companies Using q-Rung Orthopair Fuzzy Aczel–Alsina Average Aggregation Operators

Abstract

AbstractThe term “q-Rung orthopair fuzzy sets ($$q^{r}$$ q r OFSs)” refers to the collection of the most differentiated ideas for expressing fuzzy data in decision-making rules. The $$q^{r}$$ q r OFSs can gradually adapt the region of information by adjusting the parameter $$q \ge 1$$ q ≥ 1 in response to the fluctuation degree, so assisting in the generation of more numerous possibilities. Aczel–Alsina triangular norm and conorm are superior operations that may create general and adaptable working principles for aggregating arguments. To make use of $$q^{r}$$ q r OFSs and Aczel–Alsina triangular norms in “multiple attribute decision-making (MADM)” issues, a few q-rung orthopair fuzzy ($$q^{r}$$ q r OF) Aczel–Alsina aggregation operators: $$q^{r}$$ q r OF Aczel–Alsina weighted average ($$q^{r}$$ q r OFAAWA) operator, $$q^{r}$$ q r OF Aczel–Alsina order weighted average ($$q^{r}$$ q r OFAAOWA) operator, $$q^{r}$$ q r OF Aczel–Alsina hybrid average ($$q^{r}$$ q r OFAAHA) operator for aggregating $$q^{r}$$ q r OFSs are exhibited in this article to fix the MADM issues based on $$q^{r}$$ q r OFSs. Some significant properties are additionally demonstrated. A technique for taking care of the MADM issues is proposed based on these created operators. The adequacy of the suggested technique is shown by means of a numerical example on enterprise partner selection, a lot of investigations and correlations with other existing strategies. The sensitivity of the proposed aggregation operators to decision-making findings is investigated. The demonstration outcomes suggest that the suggested technique has fulfilling universality and adaptability in aggregating $$q^{r}$$ q r OF data and acquiring the correlations of criteria and the attitudes of “decision-makers (DMs)” and is doable and compelling for taking care of the MADM issues dependent on $$q^{r}$$ q r OFSs.