**6. Conclusions**

Supplier selection is very important for manufacturing companies. Choosing a suitable supplier can greatly enhance the competitiveness and vitality of the company. In modern society, the selection of an appropriate supplier often requires a comprehensive assessment of all suppliers from multiple

perspectives. Thus, supplier selection is one of the most common types of MAGDM problems in daily life. The main contributions of this paper are threefold. Firstly, we proposed the concept of *q*-RDHFS by combining DHFS with *q*-ROFS. The *q*-RDHFS can not only deal with DMs' hesitancy when determining the membership and nonmembership degrees but also gives DMs' more freedom to express their assessments. Secondly, we proposed the *q*-RDHFHM, *q*-RDHFWHM, *q*-RDHFGHM, and *q*-RDHFWGHM operators to effectively aggregate *q*-RDHFEs. Thirdly, we developed a novel method for MAGDM with *q*-rung dual hesitant fuzzy information. Considering the supplier selection problem is essentially a MAGDM issue, we also applied the proposed method to a real MAGDM problem to show its performance. Additionally, through comparative analysis the superiorities and advantages of the newly proposed method over existing methods are illustrated. Compared with the existing methods, the proposed method is more general and powerful. In addition, it has three parameters—*q*, *s*, and *t*—making the process of information aggregation more flexible. In real decision-making problems, DMs can choose the appropriate values of the parameters according to their preference. It is worth pointing out that as the newly proposed method is based on the HM operator, it mainly focuses on the interrelationship between any two *q*-RDHFEs. In future works, we should investigate more aggregation operators for fusing *q*-RDHFEs, such as the *q*-rung dual hesitant fuzzy Maclaurin symmetric mean, the *q*-rung dual hesitant fuzzy Hamy mean, and the *q*-rung dual hesitant fuzzy Muirhead mean operators, which have the ability of capturing the interrelationship among multiple *q*-RDHFEs.

**Author Contributions:** Conceptualization, Y.X.; Formal Analysis, J.W.; All the authors have participated in writing the manuscript and have revised the final version. All authors read and approved the final manuscript.

**Funding:** This work was partially supported by the National Natural Science Foundation of China (Grant number 61702023), the Humanities and Social Science Foundation of the Ministry of Education of China (Grant number 17YJC870015), and the Fundamental Research Funds for the Central Universities (Grant number 2018JBM304).

**Conflicts of Interest:** The authors declare that there is no conflict of interest regarding the publication of this paper.
