Optimal resources allocation to support the consensus reaching in group decision making

被引:8
|
作者
Fan, Sha [1 ,2 ]
Liang, Haiming [1 ,2 ]
Li, Cong-Cong [3 ]
Chiclana, Francisco [4 ,5 ]
Pedrycz, Witold [6 ,7 ,8 ]
Dong, Yucheng [1 ,2 ]
机构
[1] Sichuan Univ, Business Sch, Chengdu 610065, Peoples R China
[2] Xiangjiang Lab, Changsha 410205, Peoples R China
[3] Southwest Jiaotong Univ, Sch Econ & Management, Chengdu 610031, Peoples R China
[4] De Montfort Univ, Dept Artificial Intelligence, Leicester, England
[5] De Montfort Univ, Sch Comp Sci & Informat, Leicester, England
[6] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6G 2R3, Canada
[7] Macau Univ Sci & Technol, Inst Syst Engn, Taipa 999078, Macao, Peoples R China
[8] Istinye Univ, Res Ctr Performance & Prod Anal, Istanbul, Turkiye
基金
中国国家自然科学基金;
关键词
Group decision and negotiation; Consensus; Resources allocation; Utility function; Decision support; MINIMUM-COST; UTILITY FUNCTION; MAXIMUM-RETURN; MODELS; ADJUSTMENT; OPERATORS; FEEDBACK;
D O I
10.1016/j.inffus.2024.102451
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), the minimum cost consensus model (MCCM) to assist a group to reach a consensus with the minimum cost has gained widespread attention. However, determining the unit costs for adjusting decision makers' opinions in the MCCM is a challenging problem that limits its practical applications. Meanwhile, the MCCM is not modeled as a resources allocation problem in an explicit manner, and the opinions in the MCCM do not represent utilities/satisfactions, leading to the unclear implications of opinions' adjustments. To overcome these limitations of the MCCM, this paper proposes the optimal resources allocation consensus model (ORACM) to assist the moderator to allocate resources without determining unit costs to support consensus reaching, through the introduction of the resources allocation problem and utility functions in its modeling. Furthermore, we present a theoretical analysis framework to reveal the properties of the ORACM and the connection between the ORACM and the MCCM, justifying the theoretical advantages of the ORACM. Moreover, the ORACM is applied to the transboundary river pollution control negotiations of Sichuan's Tuojiang River, and the effectiveness and feasibility of the ORACM are further validated with detailed simulation and comparison analyses.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Consensus Reaching Process for Traditional Group Decision Making in View of the Optimal Adjustment Mechanism
    Meng, Fan-Yong
    Pedrycz, Witold
    Tang, Jie
    IEEE TRANSACTIONS ON CYBERNETICS, 2023, 53 (06) : 3748 - 3759
  • [2] Group Decision Making with Heterogeneous Preference Structures: An Automatic Mechanism to Support Consensus Reaching
    Zhang, Bowen
    Dong, Yucheng
    Herrera-Viedma, Enrique
    GROUP DECISION AND NEGOTIATION, 2019, 28 (03) : 585 - 617
  • [3] Group Decision Making with Heterogeneous Preference Structures: An Automatic Mechanism to Support Consensus Reaching
    Bowen Zhang
    Yucheng Dong
    Enrique Herrera-Viedma
    Group Decision and Negotiation, 2019, 28 : 585 - 617
  • [4] Group decision making models on allocation of resources
    Yang, Lei
    Xi, Youmin
    Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice, 1997, 17 (06): : 22 - 25
  • [5] Linguistic stochastic dominance to support consensus reaching in group decision making with linguistic distribution assessments
    Liang, Haiming
    Chen, Xia
    Li, Cong-Cong
    Zhang, Hengjie
    INFORMATION FUSION, 2021, 76 : 107 - 121
  • [6] Consensus reaching model with individual satisfactions in group decision making
    Zhang, Hengjie
    Dong, Yucheng
    Herrera-Viedma, Enrique
    2015 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2015), 2015,
  • [7] The effect of opinion evolution in consensus reaching in group decision making
    Zha, Quanbo
    Dong, Yucheng
    DATA SCIENCE AND KNOWLEDGE ENGINEERING FOR SENSING DECISION SUPPORT, 2018, 11 : 213 - 219
  • [8] Approach to reaching consensus in multiple attribute group decision making
    Xu, Ying-Jun
    Li, Dong
    Kongzhi yu Juece/Control and Decision, 2010, 25 (12): : 1810 - 1814
  • [9] A Personalized Feedback Mechanism Based on Bounded Confidence Learning to Support Consensus Reaching in Group Decision Making
    Zha, Quanbo
    Dong, Yucheng
    Zhang, Hengjie
    Chiclana, Francisco
    Herrera-Viedma, Enrique
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 51 (06): : 3900 - 3910
  • [10] Consensus evolution networks: A consensus reaching tool for managing consensus thresholds in group decision making
    Wu, Tong
    Liu, Xinwang
    Qin, Jindong
    Herrera, Francisco
    INFORMATION FUSION, 2019, 52 : 375 - 388