The power average (PA) operator can reduce the influence of unreasonable information given by biased decision makers effectively, while Heronian mean (HM) operator can take into account the correlation information between attribute variables in multiple attribute decision making (MADM). Pythagorean fuzzy set (PFS) is a useful tool to handle uncertain information, which has been widely applied in kinds of areas. In order to better infuse the Pythagorean fuzzy evaluation, in this paper we unify the advantages of the PA operator and HM operator, and present the Pythagorean fuzzy power Heronian mean (PFPHM) operator and the Pythagorean fuzzy weighted power Heronian mean (PFWPHM) operator. Some merits of the developed operators are further explored. Furthermore, on the basis of the PFWPHM operator, an approach for MADM under PFS situation is presented. Finally, a numerical case concerning investment company selection is illustrated to demonstrate the availability and feasibility of the developed approach.
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