In this paper, we investigate the multiple attribute decision making problems based on the Bonferroni mean operators with dual Pythagorean hesitant fuzzy information. Firstly, we introduce the concept and basic operations of the dual hesitant Pythagorean fuzzy sets, which is a new extension of Pythagorean fuzzy sets. Then, motivated by the idea of Bonferroni mean operators, we have developed some Bonferroni mean aggregation operators for aggregating dual hesitant Pythagorean fuzzy information. The prominent characteristic of these proposed operators are studied. Then, we have utilized these operators to develop some approaches to solve the dual hesitant Pythagorean fuzzy multiple attribute decision making problems. Finally, a practical example for supplier selection in supply chain management is given to verify the developed approach and to demonstrate its practicality and effectiveness.
In this paper, a new set of intuitionistic fuzzy aggregation operators have been introduced under the environment of intuitionistic fuzzy sets (IFSs). For this, firstly focused on some existing aggregation operators and then new operational rules known as Dombi operation have been pro- posed which make the advancement of flexibility behavior with the parameter. Based on Dombi operation laws, some new averaging and geometric aggregation operators namely, intuitionistic fuzzy Dombi weighted averaging, ordered weighted averaging and hybrid weighted averaging operator, classified as IFDWA, IFDOWA and IFDHWA operators respectively and intuitionistic fuzzy Dombi geometric, ordered weighted geometric and hybrid weighted geometric operators, labeled as IFDWG, IFDOWG and IFDHWG operators respectively have been proposed. Further, some properties such as idempotency, boundedness, monotonicity and commutative are investigated. Finally, a multi-attribute decision-making model has been developed for the proposed operators to select the best mutual fund for investment. The execution of the comparative study has been examined with the existing operators in this environment.