Consensus-reaching methods for hesitant fuzzy multiple criteria group decision making with hesitant fuzzy decision making matrices

被引:0
作者
Jie Ding
Ze-shui Xu
Hu-chang Liao
机构
[1] Sichuan University,Business School
来源
Frontiers of Information Technology & Electronic Engineering | 2017年 / 18卷
关键词
Multiple criteria group decision making; Group consensus; Consensus-reaching process; Hesitant fuzzy decision making matrices; Aggregation operators; TP13; C934;
D O I
暂无
中图分类号
学科分类号
摘要
Group decision making plays an important role in various fields of management decision and economics. In this paper, we develop two methods for hesitant fuzzy multiple criteria group decision making with group consensus in which all the experts use hesitant fuzzy decision matrices (HFDMs) to express their preferences. The aim of this paper is to present two novel consensus models applied in different group decision making situations, which are composed of consensus checking processes, consensus-reaching processes, and selection processes. All the experts make their own judgments on each alternative over multiple criteria by hesitant fuzzy sets, and then the aggregation of each hesitant fuzzy set under each criterion is calculated by the aggregation operators. Furthermore, we can calculate the distance between any two aggregations of hesitant fuzzy sets, based on which the deviation between any two experts is yielded. After introducing the consensus measure, we develop two kinds of consensus-reaching procedures and then propose two step-by-step algorithms for hesitant fuzzy multiple criteria group decision making. A numerical example concerning the selection of selling ways about ‘Trade-Ins’ for Apple Inc. is provided to illustrate and verify the developed approaches. In this example, the methods which aim to reach a high consensus of all the experts before the selection process can avoid some experts’ preference values being too high or too low. After modifying the previous preference information by using our consensus measures, the result of the selection process is much more reasonable.
引用
收藏
页码:1679 / 1692
页数:13
相关论文
共 69 条
[21]  
Xu Z.S.(2011)Distance and similarity measures for hesitant fuzzy sets Inform. Sci. 181 2128-2138
[22]  
Liao H.C.(2011)On distance and correlation measures of hesitant fuzzy information Int. J. Intell. Syst. 26 410-425
[23]  
Xu Z.S.(1965)Fuzzy sets Inform. Contr. 8 338-353
[24]  
Liao H.C.(2013)The multi-criteria hesitant fuzzy group decision making with MULTI-MOORA method Econ. Comput. Econ. Cybern. Stud. Res. 47 171-184
[25]  
Xu Z.S.(2013)A hesitant fuzzy multiple attribute group decision making approach based on TOPSIS for parts supplier selection Appl. Mech. Mater. 357–360 2730-2737
[26]  
Xia M.M.(2014)Consensus model for multiple criteria group decision making under intuitionistic fuzzy environment Knowl.-Based Syst. 57 127-135
[27]  
Liao H.C.(2015)A consensus model for group decision making with hesitant fuzzy information Int. J. Uncert. Fuzz. Knowl.-Based Syst. 23 459-480
[28]  
Xu Z.S.(2015)A decision support model for group decision making with hesitant fuzzy preference relations Knowl.-Based Syst. 86 77-101
[29]  
Zeng X.J.(2016)On Atanassov’s intuitionistic fuzzy sets in the complex plane and the field of intuitionistic fuzzy numbers IEEE Trans. Fuzzy Syst. 24 253-259
[30]  
Liao H.C.(undefined)undefined undefined undefined undefined-undefined