The probabilistic hesitant fuzzy TOPSIS method based on the regret theory and its application in investment strategy

The technique for order preference by similarity to ideal solution (TOPSIS) is a popular multi-attribute decision making method. However, the increasing uncertain information with probability and the psychological factor of regret aversion of experts in some complicated situations bring new challenges to the application of traditional TOPSIS. The probabilistic hesitant fuzzy set (P-HFS) is an effective tool to depict the hesitant fuzzy information with the corresponding probability, which can remain more information. In addition, the regret theory indicates that experts may care more about the regret values than the absolute values of alternatives under the fuzzy environment. This paper investigates a new probabilistic hesitant fuzzy TOPSIS (PHFTOPSIS) method based on the regret theory. We propose the corresponding concepts of utility function, reject-rejoice function and perceived utility value of the probabilistic hesitant fuzzy element (P-HFE). The maximum deviation model under the probabilistic hesitant fuzzy environment is presented to determine the weights of attributes. The detailed implementation process of the PHFTOPSIS method based on the regret theory is also provided. Moreover, we apply the proposed method to the investment strategy. Compared with earlier methods, the proposed method can consider both the probabilistic hesitant fuzzy information and regret aversion of experts at the same time in actual applications. A comparative analysis with traditional TOPSIS and probabilistic hesitant fuzzy weighted averaging (PHFWA) operator is further conducted to illustrate its advantages.