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Hesitant fuzzy Bonferroni means for multi-criteria decision making

Author

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  • B Zhu

    (School of Economics and Management, Southeast University, Jiangsu, China)

  • Z S Xu

    (School of Economics and Management, Southeast University, Jiangsu, China)

Abstract

Due to the desirable characteristic of the Bonferroni mean (BM) that it can capture the interrelationship between input arguments, and in order to provide the properties and the modelling capability of the BMs under hesitant fuzzy environment, we explore some new hesitant fuzzy Bonferroni means (HFBMs). The properties and the special cases of HFBMs are studied in detail. We specially define a concept of hesitant Bonferroni element (HBE), which is considered as a ‘bonding satisfaction’ factor used as a calculation unit in the HFBM. The HBE can reflect the correlation between hesitant fuzzy arguments, which makes the HFBM have particular advantages in aggregating arguments. In addition, the weighted hesitant fuzzy Bonferroni mean (WHFBM) is also proposed considering different importance degrees of input arguments. Furthermore, the procedure of multi-criteria decision making based on the WHFBM is given under hesitant fuzzy environment as typical applications, which has much sense in theory and practice for the BM.

Suggested Citation

  • B Zhu & Z S Xu, 2013. "Hesitant fuzzy Bonferroni means for multi-criteria decision making," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(12), pages 1831-1840, December.
    • Handle: RePEc:pal:jorsoc:v:64:y:2013:i:12:p:1831-1840
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    Citations

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    Cited by:

    1. Shuli Liu & Xinwang Liu, 2016. "A Sample Survey Based Linguistic MADM Method with Prospect Theory for Online Shopping Problems," Group Decision and Negotiation, Springer, vol. 25(4), pages 749-774, July.
    2. Xiaodi Liu & Zengwen Wang & Antoinette Hetzler, 2017. "HFMADM method based on nondimensionalization and its application in the evaluation of inclusive growth," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 18(4), pages 726-744, July.
    3. Runtong Zhang & Jun Wang & Xiaomin Zhu & Meimei Xia & Ming Yu, 2017. "Some Generalized Pythagorean Fuzzy Bonferroni Mean Aggregation Operators with Their Application to Multiattribute Group Decision-Making," Complexity, Hindawi, vol. 2017, pages 1-16, August.
    4. Hao Xu & Liuxin Chen & Qiongfang Li & Jianchao Yang, 2021. "A Multi-Attribute Decision Method under Uncertainty Environment Conditions—The Green Supplier Evaluation Perspective," IJERPH, MDPI, vol. 18(1), pages 1-15, January.
    5. Wei Yang & Yongfeng Pang, 2022. "T-Spherical Fuzzy Bonferroni Mean Operators and Their Application in Multiple Attribute Decision Making," Mathematics, MDPI, vol. 10(6), pages 1-33, March.
    6. Jalil Heidary Dahooie & Amir Salar Vanaki & Hamid Reza Firoozfar & Edmundas Kazimieras Zavadskas & Audrius Čereška, 2020. "An Extension of the Failure Mode and Effect Analysis with Hesitant Fuzzy Sets to Assess the Occupational Hazards in the Construction Industry," IJERPH, MDPI, vol. 17(4), pages 1-22, February.
    7. Zhang, Hong-yu & Ji, Pu & Wang, Jian-qiang & Chen, Xiao-hong, 2017. "A novel decision support model for satisfactory restaurants utilizing social information: A case study of TripAdvisor.com," Tourism Management, Elsevier, vol. 59(C), pages 281-297.
    8. Xiaorong He, 2018. "Typhoon disaster assessment based on Dombi hesitant fuzzy information aggregation operators," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 90(3), pages 1153-1175, February.
    9. Xiaoyan Zhang & Qian Yang, 2022. "A Novel Method for Decision Making by Double-Quantitative Rough Sets in Hesitant Fuzzy Systems," Mathematics, MDPI, vol. 10(12), pages 1-24, June.
    10. Guiwu Wei & Cun Wei & Jiang Wu & Hongjun Wang, 2019. "Supplier Selection of Medical Consumption Products with a Probabilistic Linguistic MABAC Method," IJERPH, MDPI, vol. 16(24), pages 1-15, December.

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