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

Abstract

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

Probabilistic Hesitant Fuzzy Decision-Theoretic Rough Set Model and Its Application in Supervision of Shared Parking

“…To show the advantages of the new model with a probabilistic hesitant fuzzy relation, the model in this paper is compared with references [18,40,41]. The evaluation values of the relation between the parking lots and criteria are represented as hesitant fuzzy elements, which are shown in Tables 15-17.…”

“…Wang et al combined several MCDM techniques with probabilistic hesitant fuzzy linguistic term sets (PHFLTSs) to implement group risk assessment in failure mode and effects analysis [17]. Wu et al constructed a probabilistic hesitant fuzzy MAGDM method based on the generalized probabilistic hesitant fuzzy Bonferroni mean (GPHFBM) operator to analyze the aggregated information, enabling decision-makers to select the proper parameters in the decision-making process [18]. Li et al proposed an integrated MAGDM method based on the best-worst method (BWM) and MULTI MOORA method with two-dimensional linguistic intuitionistic fuzzy variables (2DLIFVs) for the selection of unmanned aerial vehicle suppliers [19].…”

Cross-Efficiency Evaluation under Probabilistic Hesitant Fuzzy Environment and Its Application to the Portfolio Selection Process

“…Fuzzy theory is widely used in various fields because it can describe uncertain information. In the field of investment, interval fuzzy sets [19][20][21], hesitant fuzzy sets [22,23], intuitionistic fuzzy sets [24,25], and probabilistic hesitant fuzzy sets [18,26] are often used to describe all kinds of evaluation information.…”