An extended TODIM method and its application in the stock selection under dual hesitant fuzzy linguistic information

Uncertain information is inevitable in real life due to decision makers' limited rationality and the complexity of correlative problems. Dual hesitant fuzzy linguistic elements (DHFLEs) can collect all the information from two different viewpoints qualitatively and it has become one of the most effective tools for dealing with uncertain information. In this paper, the main contribution is to propose an extended TODIM method under dual hesitant fuzzy linguistic information and to apply this method to deal with a stock selection problem. Firstly, a new distance measure of DHFLEs is proposed for determining the deviation degree between different DHFLEs. Secondly, in order to distinguish between different DHFLEs effectively, we construct a novel score function of the DHFLE. The score function and the new distance measure are used to complete the extended TODIM method under dual hesitant fuzzy linguistic information. Finally, to show the validity and the practicability, we use the extended TODIM method to solve a practical problem of stock selection.