A GRA method for investment alternative selection under dual hesitant fuzzy environment with incomplete weight information

Dual hesitant fuzzy set (DHFS), which permits the possible membership degrees and non-membership degrees of an element having sets of values in [0,1], is considered as a powerful tool to express uncertain information in the process of multiple attribute group decision making (MAGDM). In this paper, we study the MAGDM problems in which the attribute values take the form of dual hesitant fuzzy elements and the weights of attributes and decision makers take the form of real numbers. Firstly, the normalized Hamming distance of the dual hesitant fuzzy elements is defined. Then, a new method for dealing MAGDM problems under dual hesitant fuzzy environment is proposed on the basis of grey relational analysis (GRA) theory. For the incompletely known and completely unknown information of attribute weight, some optimization models are established to determine the weights of attributes. Finally, a numerical example of investment alternative selection is given to illustrate the application of the proposed method and to demonstrate its practicality and effectiveness.