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A Novel MAGDM Technique Based on Q-rung Orthopair Fuzzy Aczel-Alsina Power Heronian Mean for Sustainable Supplier Selection in Organ Transplantation Networks for Healthcare Devices

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Abstract

Due to the intense competition in the market today, choosing of an appropriate healthcare device vendor in long-term organ transplant networks has emerged as a key issue in raising life expectancy. A complicated multi-attribute group decision-making (MAGDM) process problem with several viable alternatives and sustainable criteria may be used for evaluating sustainable healthcare equipment vendors. The q-rung orthopair fuzzy set (QROFS) is more effective at expressing ambiguous and fuzzy information since it is a generalization of intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFS). The fact that QROFSs provide a wider range of acceptable membership grades and give decision-makers more leeway to express their real thoughts is their most valued feature. The Heronian mean (HM) operator and power aggregation (PA) operator are instances of classic aggregation operators. They are preferable because they can replicate the correlations between attributes and remove the negative effects of awkward information. The Aczel-Alsina t-norms, which were put out by Aczel and Alsina in 1982, constitute a very successful and widely used method for creating any type of aggregation operators. Additionally, the parameter Φ \(\in \left( {0, + \infty } \right)\) makes the Algebraic t-norms as a special case of the Aczel-Alsina t-norms. To take the above advantages, in this article, initially, the Aczel-Alsina (AA) operational laws are combined, with power average and Heronian mean operators to propose the QROFAA power Heronian aggregation (QROFPWHA) operator and QROFAA power geometric Heronian aggregation (QROFAAFPGHA) operator. Moreover, some core characteristics and various core cases with respect to the parameters are investigated and found that some of the existing aggregation defined on AA operational laws are special cases of the suggested aggregation operators. Secondly, the weighted forms of the suggested aggregation operators are initiated. Thirdly, based on these newly aggregation operators two novel MAGDM models with unknown weights of the decision makers and attributes are initiated. Finally, an illustrated example about evaluating sustainable healthcare equipment vendors is provided to assess the effectiveness of the suggested models, and a comparison analysis is provided to support and corroborate the suggested approaches. Additionally, assessment for key parameters in the proposed models is carried out to evaluate the implications on results.

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Funding

This paper is supported by Taishan Scholars Project of Shandong Province, Shandong Provincial Key Research and Development Program(Major Scientific and Technological Innovation Project) (Nos. 2021SFGC0102, 2020CXGC010110), Major bidding projects of National Social Science Fund of China (No. 19ZDA080).

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Authors and Affiliations

  1. School of Business Administration, Shandong Women’s University, Jinan, 250300, Shandong, China

    Peide Liu

  2. Department of Mathematics and Statistics, University of Haripur, Haripur, KPK, Pakistan

    Qaisar Khan

  3. Aziz Bhatti Shaheed Teaching Hospital Gujrat, Punjab, Pakistan

    Ayesha Jamil

  4. Department of Public Health and Nutrition, University of Haripur, Haripur, KPK, Pakistan

    Ijaz Ul Haq

  5. Department of Mathematics, Abbottabad University of Science and Technology, Abbottabad, KPK, Pakistan

    Fawad Hussain & Zia Ullah

  6. Shandong Key Laboratory of New Smart Media, Jinan, 250014, Shandong, China

    Peide Liu

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Liu, P., Khan, Q., Jamil, A. et al. A Novel MAGDM Technique Based on Q-rung Orthopair Fuzzy Aczel-Alsina Power Heronian Mean for Sustainable Supplier Selection in Organ Transplantation Networks for Healthcare Devices. Int. J. Fuzzy Syst. 26, 121–153 (2024). https://doi.org/10.1007/s40815-023-01580-4

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