Based on linguistic evaluations, a linguistic threeway decision method is proposed. First, the alternatives are rated in linguistic forms and divided into acceptance, rejection and uncertainty regions. Secondly, the l...Based on linguistic evaluations, a linguistic threeway decision method is proposed. First, the alternatives are rated in linguistic forms and divided into acceptance, rejection and uncertainty regions. Secondly, the linguistic three-way group decision steps are provided. Specifically, the experts determine the lower bound and upper bound of the uncertainty region, respectively. When the evaluation is superior to the upper bound, the corresponding alternative is put into the acceptance region directly. Similarly, when the evaluation is inferior to the lower bound, the corresponding alternative is put into the rejection region directly, and the remaining alternatives are put into the uncertain region. Moreover, the objects in the uncertainty region are especially discussed. The linguistic terms are transformed into fuzzy numbers and then aggregated. Finally, a recommendation example is provided to illustrate the practicality and validity of the proposed method.展开更多
基金The National Natural Science Foundation of China(No.71171048,71371049)the Scientific Innovation Research of College Graduates in Jiangsu Province(No.KYLX15-0190)the Scientific Research Foundation of Graduate School of Southeast University(No.YBJJ1567)
文摘Based on linguistic evaluations, a linguistic threeway decision method is proposed. First, the alternatives are rated in linguistic forms and divided into acceptance, rejection and uncertainty regions. Secondly, the linguistic three-way group decision steps are provided. Specifically, the experts determine the lower bound and upper bound of the uncertainty region, respectively. When the evaluation is superior to the upper bound, the corresponding alternative is put into the acceptance region directly. Similarly, when the evaluation is inferior to the lower bound, the corresponding alternative is put into the rejection region directly, and the remaining alternatives are put into the uncertain region. Moreover, the objects in the uncertainty region are especially discussed. The linguistic terms are transformed into fuzzy numbers and then aggregated. Finally, a recommendation example is provided to illustrate the practicality and validity of the proposed method.
