Consensus models with aggregation operators for minimum quadratic cost in group decision making

被引:11
作者
Zhang, Ruonan [1 ]
Huang, Jing [1 ]
Xu, Yejun [2 ]
Herrera-Viedma, Enrique [3 ,4 ]
机构
[1] Hohai Univ, Business Sch, Nanjing 211100, Peoples R China
[2] Tianjin Univ, Coll Management & Econ, Tianjin 300072, Peoples R China
[3] Univ Granada, Andalusian Res Inst Data Sci & Computat Intellige, Granada 18071, Spain
[4] Univ Teknol Malaysia, Fac Engn, Sch Comp, Bahru 81310, Johor, Malaysia
基金
中国国家自然科学基金;
关键词
Aggregation operator; Group decision making; Minimum cost consensus model; FUZZY PREFERENCE-RELATION; FEEDBACK MECHANISM; SOCIAL NETWORK; CONSISTENCY; ADJUSTMENT; ALGORITHM;
D O I
10.1007/s10489-021-02948-5
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In group decision making (GDM), to facilitate an acceptable consensus among the experts from different fields, time and resources are paid for persuading experts to modify their opinions. Thus, consensus costs are important for the GDM process. Notwithstanding, the unit costs in the common linear cost functions are always fixed, yet experts will generally express more resistance if they have to make more compromises. In this study, we use the quadratic cost functions, the marginal costs of which increase with the opinion changes. Aggregation operators are also considered to expand the applications of the consensus methods. Moreover, this paper further analyzes the minimum cost consensus models under the weighted average (WA) operator and the ordered weighted average (OWA) operators, respectively. Corresponding approaches are developed based on strictly convex quadratic programming and some desirable properties are also provided. Finally, some examples and comparative analyses are furnished to illustrate the validity of the proposed models.
引用
收藏
页码:1370 / 1390
页数:21
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