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Multicriteria Decision Making Based on Archimedean Bonferroni Mean Operators of Hesitant Fermatean 2-Tuple Linguistic Terms

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  • Huijuan Wang
  • Xin Wang
  • Lidong Wang

Abstract

The study is concerned with the representation and aggregation of complex uncertainty information. First, the concept of hesitant Fermatean 2-tuple linguistic sets (HF2TLSs) is introduced for characterizing an individual’s imprecision preferences and assessing information by combining 2-tuple linguistic terms and Fermatean fuzzy sets. The advantage of hesitant Fermatean 2-tuple linguistic information is that it can handle higher levels of uncertainty and express the decision-makers’ hesitancy. Second, we extend Bonferroni mean (BM) operators under the background of HF2TLSs for the sake of their application in information fusion and decision making. The Archimedean t -norm and s -norm- (ATS-) based hesitant Fermatean 2-tuple linguistic weighted Bonferroni mean (A-HF2TLWBM) operator and the ATS-based hesitant Fermatean 2-tuple linguistic weighted geometric Bonferroni mean (A-HF2TLWGBM) operator are developed by considering the interrelationship between any two variables. The main benefit of the proposed operators is that these operators deliver more complete and flexible results compared to existing methods. Moreover, some fundamental properties and special cases are examined by adjusting parameter values. Finally, an approach is designed as a support for handling decision making problems, and an example regarding investment selection is provided to demonstrate the practicality of the designed method with a detailed discussion of parameter influence and comparisons with the existing methods.

Suggested Citation

  • Huijuan Wang & Xin Wang & Lidong Wang, 2019. "Multicriteria Decision Making Based on Archimedean Bonferroni Mean Operators of Hesitant Fermatean 2-Tuple Linguistic Terms," Complexity, Hindawi, vol. 2019, pages 1-19, December.
    • Handle: RePEc:hin:complx:5705907
    DOI: 10.1155/2019/5705907
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    References listed on IDEAS

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    1. Dheeraj Kumar Joshi & Ismat Beg & Sanjay Kumar, 2018. "Hesitant Probabilistic Fuzzy Linguistic Sets with Applications in Multi-Criteria Group Decision Making Problems," Mathematics, MDPI, vol. 6(4), pages 1-20, March.
    2. Wancheng Zhang & Yejun Xu & Huimin Wang, 2016. "A consensus reaching model for 2-tuple linguistic multiple attribute group decision making with incomplete weight information," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(2), pages 389-405, January.
    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. Peide Liu & Peng Wang, 2017. "Some Improved Linguistic Intuitionistic Fuzzy Aggregation Operators and Their Applications to Multiple-Attribute Decision Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 817-850, May.
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    Cited by:

    1. Ayyildiz, Ertugrul, 2022. "Fermatean fuzzy step-wise Weight Assessment Ratio Analysis (SWARA) and its application to prioritizing indicators to achieve sustainable development goal-7," Renewable Energy, Elsevier, vol. 193(C), pages 136-148.
    2. Wenying Wu & Zhiwei Ni & Feifei Jin & Jian Wu & Ying Li & Ping Li, 2021. "Investment Selection Based on Bonferroni Mean under Generalized Probabilistic Hesitant Fuzzy Environments," Mathematics, MDPI, vol. 9(1), pages 1-21, January.
    3. Dong, Weiwei & Zhao, Guohua & Yüksel, Serhat & Dinçer, Hasan & Ubay, Gözde Gülseven, 2022. "A novel hybrid decision making approach for the strategic selection of wind energy projects," Renewable Energy, Elsevier, vol. 185(C), pages 321-337.

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