A decentralized feedback mechanism with compromise behavior for large-scale group consensus reaching process with application in smart logistics supplier selection

被引:26
作者
Gai, Tiantian [1 ,2 ]
Cao, Mingshuo [1 ,2 ]
Chiclana, Francisco [3 ,5 ]
Wu, Jian [1 ,2 ]
Liang, Changyong [4 ]
Herrera-Viedma, Enrique [5 ,6 ]
机构
[1] Shanghai Maritime Univ, Sch Econ & Management, Shanghai 201306, Peoples R China
[2] Shanghai Maritime Univ, Ctr Artificial Intelligence & Decis Sci, Shanghai 201306, Peoples R China
[3] De Montfort Univ, Fac Comp Engn & Media, Inst Artificial Intelligence, Leicester LE1 9BH, Leics, England
[4] Hefei Univ Technol, Sch Management, Hefei 230009, Peoples R China
[5] Univ Granada, Andalusian Res Inst Data Sci & Computat Intellige, Granada 18071, Spain
[6] King Abdulaziz Univ, Fac Engn, Dept Elect & Comp Engn, Jeddah 21589, Saudi Arabia
基金
中国国家自然科学基金;
关键词
Large-scale group decision making; Consensus; Decentralized feedback mechanism; Smart logistics; GROUP DECISION-MAKING; SOCIAL NETWORK ANALYSIS; NONCOOPERATIVE BEHAVIORS; LINGUISTIC INFORMATION; BOUNDED CONFIDENCE; MODEL; FRAMEWORK; PREFERENCES; SYSTEM;
D O I
10.1016/j.eswa.2022.117547
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes a decentralized feedback mechanism to help large-scale decision makers (DMs) reach consensus considering the limited compromise behavior of subgroups. First, a novel decentralized opinion interaction mechanism is designed to identify the most inconsistent subgroups pair in the group and make them interact with each other. Then it is different from the centralized interaction mechanism, which adopts the aggregation of the opinions of other subgroups. The former is suitable for situations with low initial consensus level while the later is for high consensus level. Secondly, the compromise behavior of subgroups in the feedback process is explored, and then the concept of `compromise threshold' (CT) is defined to analyze the limited compromise behavior of subgroups. Finally, an illustrative example regarding the smart logistics supplier selection (SLEC) is described to demonstrate the effectiveness and advantages of the proposed mechanism.
引用
收藏
页数:15
相关论文
共 71 条
[61]  
2-L
[62]   ON ORDERED WEIGHTED AVERAGING AGGREGATION OPERATORS IN MULTICRITERIA DECISION-MAKING [J].
YAGER, RR .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1988, 18 (01) :183-190
[63]   Induced ordered weighted averaging operators [J].
Yager, RR ;
Filev, DP .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 1999, 29 (02) :141-150
[64]   Consensus reaching for MAGDM with multi-granular hesitant fuzzy linguistic term sets: a minimum adjustment-based approach [J].
Yu, Wenyu ;
Zhang, Zhen ;
Zhong, Qiuyan .
ANNALS OF OPERATIONS RESEARCH, 2021, 300 (02) :443-466
[65]   A minimum adjustment consensus framework with compromise limits for social network group decision making under incomplete information [J].
Yuan, Yuxiang ;
Cheng, Dong ;
Zhou, Zhili .
INFORMATION SCIENCES, 2021, 549 :249-268
[66]   A Feedback Mechanism With Bounded Confidence- Based Optimization Approach for Consensus Reaching in Multiple Attribute Large-Scale Group Decision-Making [J].
Zha, Quanbo ;
Liang, Haiming ;
Kou, Gang ;
Dong, Yucheng ;
Yu, Shui .
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2019, 6 (05) :994-1006
[67]   Public transportation development decision-making under public participation: A large-scale group decision-making method based on fuzzy preference relations [J].
Zhang, Linling ;
Yuan, Jinjian ;
Gao, Xinyu ;
Jiang, Dawei .
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2021, 172
[68]   Personalized Individual Semantics-Based Consistency Control and Consensus Reaching in Linguistic Group Decision Making [J].
Zhang, Zhen ;
Li, Zhuolin .
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2022, 52 (09) :5623-5635
[69]   Consensus reaching for group decision making with multi-granular unbalanced linguistic information: A bounded confidence and minimum adjustment-based approach [J].
Zhang, Zhen ;
Li, Zhuolin ;
Gao, Yuan .
INFORMATION FUSION, 2021, 74 :96-110
[70]   Assignment of attribute weights with belief distributions for MADM under uncertainties [J].
Zhou, Mi ;
Liu, Xin-Bao ;
Chen, Yu-Wang ;
Qian, Xiao-Fei ;
Yang, Jian-Bo ;
Wu, Jian .
KNOWLEDGE-BASED SYSTEMS, 2020, 189