On Developing Pythagorean Fuzzy Dombi Geometric Bonferroni Mean Operators with Their Application to Multicriteria Decision Making

In modeling real-world decision making problems, interrelationship among parameters for describing attributes is usually needed to consider. Bonferroni mean possesses that very characteristic to establish the correlation among parameters of the attributes. Furthermore, Dombi operations have an excellent power of flexibility in information aggregation process due to the presence of general parameters associated with t-conorm and t-norm. Considering both the advantages, in this study, geometric Bonferroni mean operator is combined with Dombi operations to propose new aggregation operators under Pythagorean fuzzy environment, viz., Pythagorean fuzzy Dombi geometric Bonferroni mean and Pythagorean fuzzy weighted Dombi geometric Bonferroni mean operators. Some of the properties and special cases of the newly developed operators are investigated. Due to the presence of several parameters, unlike existing approaches, the proposed operators are very much capable of incorporating interrelationship among input arguments as well as optimistic or pessimistic view of the decision makers based on Pythagorean fuzzy decision situations. Using those operators, a methodology for solving multicriteria decision making problems having interrelated arguments is presented. The developed method is applied to a problem relating to supply chain management and solved. The effects of different parameters associated with the model are investigated. Finally, achieved solutions are compared with the existing methods to establish the efficiency of the proposed method.