Investment Selection Based on Bonferroni Mean under Generalized Probabilistic Hesitant Fuzzy Environments

In investment selection problems, the existence of contingency and uncertainty may result in loss attribute information. Then, how to make proper decision-making will be a tricky proposition. this work, multiattribute group decision making (MAGDM) method based on generalized probabilistic hesitant fuzzy Bonferroni mean (GPHFBM) operator is constructed, which enables decision-makers select parameters process. Firstly, GPHFBM proposed by combining Archimedean norm. Secondly, five excellent properties are discussed detail. view applications, we further develop some special aggregation operators for with various values b, d additive g(t). Finally, propose MAGDM analyze aggregated A case study social insurance funds given depict validity reasonability method. Ultimately, company X4 selected as best comprehensive indicator.