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Consensus reaching for MAGDM with multi-granular hesitant fuzzy linguistic term sets: a minimum adjustment-based approach

Author

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  • Wenyu Yu

    (Dalian University of Technology)

  • Zhen Zhang

    (Dalian University of Technology)

  • Qiuyan Zhong

    (Dalian University of Technology)

Abstract

Due to the uncertainty of decision environment and differences of decision makers’ culture and knowledge background, multi-granular HFLTSs are usually elicited by decision makers in a multi-attribute group decision making (MAGDM) problem. In this paper, a novel consensus model is developed for MAGDM based on multi-granular HFLTSs. First, it is defined the group consensus measure based on the fuzzy envelope of multi-granular HFLTSs. Afterwards, an optimization model which aims to minimize the overall adjustment amount of decision makers’ preference is established. Based on the model, an iterative algorithm is devised to help decision makers reach consensus in MAGDM with multi-granular HFLTSs. Numerical results demonstrate the characteristics of the proposed consensus model.

Suggested Citation

  • Wenyu Yu & Zhen Zhang & Qiuyan Zhong, 2021. "Consensus reaching for MAGDM with multi-granular hesitant fuzzy linguistic term sets: a minimum adjustment-based approach," Annals of Operations Research, Springer, vol. 300(2), pages 443-466, May.
    • Handle: RePEc:spr:annopr:v:300:y:2021:i:2:d:10.1007_s10479-019-03432-7
    DOI: 10.1007/s10479-019-03432-7
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    References listed on IDEAS

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    1. Wen-Tao Guo & Van-Nam Huynh & Songsak Sriboonchitta, 2017. "A proportional linguistic distribution based model for multiple attribute decision making under linguistic uncertainty," Annals of Operations Research, Springer, vol. 256(2), pages 305-328, September.
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    3. Bowen Zhang & Yucheng Dong & Enrique Herrera-Viedma, 2019. "Group Decision Making with Heterogeneous Preference Structures: An Automatic Mechanism to Support Consensus Reaching," Group Decision and Negotiation, Springer, vol. 28(3), pages 585-617, June.
    4. Wu-E Yang & Chao-Qun Ma & Zhi-Qiu Han, 2017. "Linguistic multi-criteria decision-making with representing semantics by programming," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(2), pages 225-235, January.
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    Cited by:

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    2. Fu Zhang & Weimin Ma, 2023. "Study on Chaotic Multi-Attribute Group Decision Making Based on Weighted Neutrosophic Fuzzy Soft Rough Sets," Mathematics, MDPI, vol. 11(4), pages 1-19, February.
    3. Tiantian Gai & Mingshuo Cao & Francisco Chiclana & Zhen Zhang & Yucheng Dong & Enrique Herrera-Viedma & Jian Wu, 2023. "Consensus-trust Driven Bidirectional Feedback Mechanism for Improving Consensus in Social Network Large-group Decision Making," Group Decision and Negotiation, Springer, vol. 32(1), pages 45-74, February.
    4. Yangjingjing Zhang & Xia Chen & Mengting Gao & Yucheng Dong, 2024. "Maximum Utility Consensus with Inequity Aversion in Social Network Group Decision Making," Group Decision and Negotiation, Springer, vol. 33(5), pages 1115-1142, October.
    5. Junliang Du & Sifeng Liu & Yong Liu & Liangyan Tao, 2023. "Multi-criteria Large-Scale Group Decision-Making in Linguistic Contexts: A Perspective of Conflict Analysis and Resolution," Group Decision and Negotiation, Springer, vol. 32(1), pages 177-207, February.
    6. Hengjie Zhang & Wenfeng Zhu & Xin Chen & Yuzhu Wu & Haiming Liang & Cong-Cong Li & Yucheng Dong, 2024. "Managing flexible linguistic expression and ordinal classification-based consensus in large-scale multi-attribute group decision making," Annals of Operations Research, Springer, vol. 341(1), pages 95-148, October.
    7. Zhen Zhang & Zhuolin Li, 2023. "Consensus-based TOPSIS-Sort-B for multi-criteria sorting in the context of group decision-making," Annals of Operations Research, Springer, vol. 325(2), pages 911-938, June.
    8. Chen, Xiaohong & Yang, Shuhan & Hu, Dongbin & Li, Xihua, 2024. "Sustainable mining method selection by a multi-stakeholder collaborative multi-attribute group decision-making method," Resources Policy, Elsevier, vol. 92(C).
    9. Krishankumar, Raghunathan & Pamucar, Dragan & Deveci, Muhammat & Aggarwal, Manish & Ravichandran, Kattur Soundarapandian, 2022. "Assessment of renewable energy sources for smart cities’ demand satisfaction using multi-hesitant fuzzy linguistic based choquet integral approach," Renewable Energy, Elsevier, vol. 189(C), pages 1428-1442.

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