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Probabilistic double hierarchy linguistic term set and its use in designing an improved VIKOR method: The application in smart healthcare

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  • Xunjie Gou
  • Zeshui Xu
  • Huchang Liao
  • Francisco Herrera

Abstract

Double hierarchy hesitant fuzzy linguistic term set (DHHFLTS) can be used to express complex linguistic information by combining two hierarchy linguistic term sets with 2-tuple linguistic structures. In decision-making processes, experts’ assessment information may often be represented by some possible double hierarchy hesitant fuzzy linguistic elements (DHHFLEs) or some DHHFLEs with probability information, and we cannot ignore these probabilities when they are directly provided or aggregated by the experts’ assessments. As we are aware that representing probability information is a new improvement and challenge for DHHFLTSs, this paper defines a novel and more general concept named probabilistic double hierarchy linguistic term set (PDHLTS). Then, to propose some more reasonable operations and a distance measure of PDHLTSs, we develop an adjustment method to ensure that two PDHLTSs have same probability distribution. Additionally, this paper develops an extended probabilistic double hierarchy linguistic VIKOR method by improving the traditional VIKOR method. Moreover, the advantages and practicality of the proposed method are demonstrated by applying it to solve a practical multiple criteria decision-making problem involving smart healthcare. Finally, we make some comparative analyses, as well as discussing possible directions for future studies.

Suggested Citation

  • Xunjie Gou & Zeshui Xu & Huchang Liao & Francisco Herrera, 2021. "Probabilistic double hierarchy linguistic term set and its use in designing an improved VIKOR method: The application in smart healthcare," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(12), pages 2611-2630, December.
    • Handle: RePEc:taf:tjorxx:v:72:y:2021:i:12:p:2611-2630
    DOI: 10.1080/01605682.2020.1806741
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    Cited by:

    1. Ruichen Zhang & Zeshui Xu & Xunjie Gou, 2023. "ELECTRE II method based on the cosine similarity to evaluate the performance of financial logistics enterprises under double hierarchy hesitant fuzzy linguistic environment," Fuzzy Optimization and Decision Making, Springer, vol. 22(1), pages 23-49, March.
    2. Wei Huang & Peiqi Hu & Fu-Sheng Tsai & Yinke Liu & Yu Huang, 2022. "Smart Sales Empower Small Farmers: An Integrated Matching Method between Suppliers and Consumers Based on the Information Axiom," Sustainability, MDPI, vol. 14(24), pages 1-20, December.
    3. Hua Shi & Lin Huang & Ke Li & Xiang-Hu Wang & Hu-Chen Liu, 2022. "An Extended Multi-Attributive Border Approximation Area Comparison Method for Emergency Decision Making with Complex Linguistic Information," Mathematics, MDPI, vol. 10(19), pages 1-16, September.
    4. Sidong Xian & Ke Qing & Ling Tang & Huilan Pan, 2023. "A Multi-criteria Group Decision Making Based on Possibility Degree Matrix and $$\mathbb {ZPDHL}$$ ZPDHL -VIKOR Method," Group Decision and Negotiation, Springer, vol. 32(3), pages 633-666, June.
    5. Zhao, Meng & Xu, Chang & Zhao, Wenxian & Lin, Mingwei, 2023. "New energy vehicle online selection method considering attribute compensation relationship and aspiration strength," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    6. Song, Yongming & Li, Yanhong & Zhu, Hongli & Li, Guangxu, 2023. "A decision support model for buying battery electric vehicles considering consumer learning and psychological behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).

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