Affiliations: [a] School of Public Policy and Administration, Nanchang University, Nanchang, P. R. China
| [b] School of Economics and Management, Tongji University, Shanghai, China
| [c] School of Mathematics and Computer Sciences, Nanchang University, Nanchang, P. R. China
Correspondence:
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Corresponding author. Xianghong Zhu, School of Mathematics and Computer Sciences, Nanchang University, Nanchang 330031, P. R. China. E-mail: [email protected].
Abstract: This research proposes a new method to solve group decision-making(GDM) problems with intuitionistic fuzzy preference relations(IFPRs). First, a new definition of multiplicative consistency of IFPR is presented to address the defects of the existing consistency definitions. Then, two programming models are established to obtain the most optimistic and pessimistic consistent IFPRs and corresponding intuitionistic fuzzy priority weights. Also, in order to improve the accuracy of aggregate information, a new method to determine the weights of decision-makers(DMs) is offered by considering the interaction among DMs. Subsequently, by combining the vagueness and non-vagueness of the aggregated information, a multiplicative consistency definition of the collective IFPR is provided. Moreover, to simplify the GDM process, a programming model for solving the priority weight is established, which effectively avoids the consistency test and correction of IFPRs. Finally, the values of the proposed method are illustrated by comparative analysis.
