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Two-sided matching decision-making model with hesitant fuzzy preference information for configuring cloud manufacturing tasks and resources

Author

Listed:
  • Baodong Li

    (Chongqing University)

  • Yu Yang

    (Chongqing University)

  • Jiafu Su

    (Chongqing Technology and Business University)

  • Zhichao Liang

    (Chongqing University)

  • Sheng Wang

    (Chongqing University)

Abstract

Owing to the complexity of socio-economic environments and the fuzziness of human cognition, information of cognitive preference provided by decision-making organizations composed of many experts is often hesitant and fuzzy. In consequence, for the sake of addressing the hesitance and fuzziness of preference information for the configuration of tasks and resources in cloud manufacturing, a decision-making model of a two-sided matching considering a bidirectional projection under preference information of hesitant fuzzy is put forward. Primarily, this paper describes the problem of two-sided matching and introduces the hesitant fuzzy set. Afterwards, according to preference information given by matching agents using the hesitant fuzzy element, the evaluation matrix is constructed. Meanwhile, the bidirectional projection technology and TOPSIS method are combined to calculate the closeness degree matrix. Further, by introducing the constraint of the stable matching, a decision-making model of a two-sided matching for maximizing the closeness degree of two-sided matching agents is constructed, and the optimal configuration results are obtained by the solving of the model. Subsequently, the illustrative case is provided to validate the rationality and effectiveness of the presented model in solving the configuration for cloud manufacturing tasks and resources. Also, the stability in the proposed configuration results is illustrated by making a sensitivity analysis. Further, the reliability in the given solving process is demonstrated through performing a comparative analysis, as well as the advantages in the proposed model is also discussed. It shows that this developed model can give stable configuration results and also provide a matching approach for different agents under an uncertain environment.

Suggested Citation

  • Baodong Li & Yu Yang & Jiafu Su & Zhichao Liang & Sheng Wang, 2020. "Two-sided matching decision-making model with hesitant fuzzy preference information for configuring cloud manufacturing tasks and resources," Journal of Intelligent Manufacturing, Springer, vol. 31(8), pages 2033-2047, December.
    • Handle: RePEc:spr:joinma:v:31:y:2020:i:8:d:10.1007_s10845-020-01552-7
    DOI: 10.1007/s10845-020-01552-7
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    References listed on IDEAS

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    1. Xiahui Liu & Liqun Zhang & Qianwang Deng & Meng Li & Chao Jiang, 2024. "Bilateral matching for collaborative remanufacturing services based on multi-attribute preferences and mutual interactions," Journal of Intelligent Manufacturing, Springer, vol. 35(3), pages 1353-1372, March.
    2. Luo, Zunhao & Wang, Dujuan & Yin, Yunqiang & Ignatius, Joshua & Cheng, T.C.E., 2025. "Service composition and optimal selection in cloud manufacturing under event-dependent distributional uncertainty of manufacturing capabilities," European Journal of Operational Research, Elsevier, vol. 325(2), pages 281-302.
    3. Mei Cai & Suqiong Hu & Ya Wang & Jingmei Xiao, 2022. "A Dynamic Social Network Matching Model for Virtual Power Plants and Distributed Energy Resources with Probabilistic Linguistic Information," Sustainability, MDPI, vol. 14(22), pages 1-33, November.
    4. Li Xiong & Chengwen Wang & Zhaoran Xu, 2022. "Supply and demand matching model of P2P sharing accommodation platforms considering fairness," Electronic Commerce Research, Springer, vol. 22(3), pages 951-978, September.
    5. Chunhua Tang & Shuangyao Zhao & Han Su & Binbin Chen, 2026. "A QoS and sustainability-driven two-stage service composition method in cloud manufacturing: combining clustering and bi-objective optimization," Journal of Global Optimization, Springer, vol. 94(2), pages 481-516, February.

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