A decision support model for group decision making with intuitionistic fuzzy linguistic preferences relations

被引:0
作者
Feifei Jin
Zhiwei Ni
Lidan Pei
Huayou Chen
Yaping Li
Xuhui Zhu
Liping Ni
机构
[1] Hefei University of Technology,School of Management
[2] Ministry of Education,Key Laboratory of Process Optimization and Intelligent Decision
[3] Anhui University,Making
[4] Ohio University,School of Mathematical Sciences
来源
Neural Computing and Applications | 2019年 / 31卷
关键词
Group decision making; Intuitionistic fuzzy linguistic preference relation; Multiplicative consistency; Consensus; Decision support model;
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中图分类号
学科分类号
摘要
As a new preference structure, the intuitionistic fuzzy linguistic preference relation (IFLPR) was introduced to efficiently cope with situations in which the membership degree and non-membership degree are represented as linguistic terms. For group decision making (GDM) problems with IFLPRs, two significant and challenging issues are individual consistency and group consensus before deriving the reliable priority weights of alternatives. In this paper, a novel decision support model is investigated to simultaneously deal with the individual consistency and group consensus for GDM with IFLPRs. First, the concepts of multiplicative consistency and weak transitivity for IFLPRs are introduced and followed by a discussion of their desirable properties. Then, a transformation approach is developed to convert the normalized intuitionistic fuzzy priority weights into multiplicative consistent IFLPR. Based on the distance of IFLPRs, the consistency index, individual consensus degree and group consensus degree for IFLPRs are further defined. In addition, two convergent automatic iterative algorithms are proposed in the investigated decision support model. The first algorithm is utilized to convert an unacceptable multiplicative consistent IFLPR to an acceptable one. The second algorithm can assist the group decision makers to achieve a predefined consensus level. The main characteristic of the investigated decision support model is that it guarantees each IFLPR is still acceptable multiplicative consistent when the predefined consensus level is achieved. Finally, several numerical examples are provided, and comparative analyses with existing approaches are performed to demonstrate the effectiveness and practicality of the investigated model.
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页码:1103 / 1124
页数:21
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