With respect to group decision making (GDM) problem with uncertain additive linguistic preference relations (UALPRs), we investigate the efficient aggregation of the uncertain additive linguistic preference information. First, we introduce two measures to assess the consistency level and the consensus level of uncertain additive linguistic preference information, respectively, and study some of their desirable properties. Then, based on both the two measures, we propose a coinduced uncertain linguistic ordered weighted averaging (IULOWA) operator, called the consistency and consensus coinduced uncertain linguistic ordered weighted averaging (C2-IULOWA) operator, to aggregate individual uncertain additive linguistic preference information, in which the consistency level and the consensus level synergistically serve as inducing variables and then guide the determination of the associated weights. We have proved the collective uncertain linguistic preference information aggregated by the C2-IULOWA operator that can maintain the fundamental properties of preference relation, such as indifference, reciprocity, and transitivity. By using the C2-IULOWA operator, we develop a direct GDM approach with UALPRs. Finally, an illustrative example on the selection of chief quality officer is used to demonstrate the effectiveness and rationalitly of the developed approach.
Abstract. In order to help enterprises to select the appropriate logistics suppliers, this paper used the fuzzy gray relation analysis method for logistics supplier evaluation. In order to fully consider the expert opinion, the hesitation fuzzy set was introduced and the grey relation analysis method was combined with it. In order to improve the scientific in decision, a set of objective combined with subjection indicators of logistics suppliers was also proposed. Finally, an example is given to illustrate the feasibility and effectiveness of the method.
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