Affiliations: [a] College of Management Science and Engineering, Shanxi University of Finance and Economics, Taiyuan, China
| [b]
Tai yuan University, China
| [c] School of Management and Economics, Beijing Institute of Technology, Beijing, China
Correspondence:
[*]
Corresponding authors. Guohua Qu and Weihua Qu, College of Management Science and Engineering, Shanxi University of Finance and Economics 030006, China. Tel.: +86 3517666466; Fax: +86 3517666868; E-mails: qugh@sxufe.edu.cn (G. Qu), quwh@sxufe.edu.cn (W. Qu).
Abstract: (DHFNs) are very suitable to be used for depicting membership function and non-membership function in uncertain event. Motivated by the idea of Shapley-Choquet integral [Meng et al. Generalized hesitant fuzzy generalized Shapley-Choquet integral operators and their application in decision making, International Journal of Fuzzy Systems 16(3) (2014), 400–410], in this paper we develop two Shapley generalized dual hesitant fuzzy generalized Choquet integral operators which globally consider the importance of elements in a set, and the correlations among them. Some important properties of the two operators are examined and apply them to develop an approach to dual hesitant fuzzy multi-attribute decision making with incomplete weight information. Moreover, A new distance measure of DHFSs is defined. If the information about the weights of attributes is incompletely known, the model for the optimal fuzzy measure on attribute set is established Finally, two numerical examples are given in solving decision making problems and the results demonstrate the feasibility and effectiveness of using the two Shapley generalized dual hesitant fuzzy generalized Choquet integral operators.
