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;
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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.
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页码:1679 / 1692
页数:13
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[1]  
Atanassov K.(1989)Interval valued intuitionistic fuzzy sets Fuzzy Sets Syst. 31 343-349
[2]  
Gargov G.(2016)Analysis of flood risk management strategies based on a group decision making process via interval-valued intuitionistic fuzzy numbers Water Resour. Manag. 30 1903-1921
[3]  
Azarnivand A.(2010)Analyzing consensus approaches in fuzzy group decision making: advantages and drawbacks Soft Comput. 14 451-463
[4]  
Malekian A.(2015)Fuzzy decision making and consensus: challenges J. Intell. Fuzzy Syst. 29 1109-1118
[5]  
Cabrerizo F.J.(2013)Correlation coefficients of hesitant fuzzy sets and their applications to clustering analysis Appl. Math. Model. 37 2197-2211
[6]  
Moreno J.M.(2016)Alpha beta-statistical convergence and strong alpha beta-convergence of order gamma for a sequence of fuzzy numbers J. Comput. Anal. Appl. 21 228-236
[7]  
Pérez I.J.(2007)A consensus model for group decision making with incomplete fuzzy preference relations IEEE Trans. Fuzzy Syst. 15 863-877
[8]  
Cabrerizo F.J.(2010)Environmental protection effect of the policy of replacement of household electrical appliances and the electronic waste treatment Ecol. Econ. 6 164-167
[9]  
Chiclana F.(2014)Some new hybrid weighted aggregation operators under hesitant fuzzy multi-criteria decision making environment J. Intell. Fuzzy Syst. 26 1601-1617
[10]  
Al-Hmouz R.(2015)Extended hesitant fuzzy hybrid weighted aggregation operators and their application in decision making Soft Comput. 19 2551-2564