Research article Special Issues

Gamified approach towards optimizing supplier selection through Pythagorean Fuzzy soft-max aggregation operators for healthcare applications

  • Received: 16 September 2023 Revised: 13 December 2023 Accepted: 20 December 2023 Published: 19 February 2024
  • MSC : 03E72, 90B50, 94D05

  • The soft-max function, a well-known extension of the logistic function, has been extensively utilized in numerous stochastic classification methodologies, such as linear differential analysis, soft-max extrapolation, naive Bayes detectors, and neural networks. The focus of this study is the development of soft-max based fuzzy aggregation operators (AOs) for Pythagorean fuzzy sets (PyFS), capitalizing on the benefits provided by the soft-max function. In addition to introducing these novel AOs, we also present a comprehensive approach to multi-attribute decision-making (MADM) that employs the proposed operators. To demonstrate the efficacy and applicability of our MADM method, we applied it to a real-world problem involving Pythagorean fuzzy data. The analysis of supplier selection has been extensively examined in many academic works as a crucial component of supply chain management (SCM), recognised as a significant MADM challenge. The process of choosing healthcare suppliers is a pivotal element that has the potential to greatly influence the efficacy and calibre of healthcare provisions. In addition, we given a numerical example to rigorously evaluate the accuracy and dependability of the proposed procedures. This examination demonstrates the effectiveness and potential of our proposed soft-max based AOs and their applicability in Pythagorean fuzzy environments.

    Citation: Sana Shahab, Mohd Anjum, Ashit Kumar Dutta, Shabir Ahmad. Gamified approach towards optimizing supplier selection through Pythagorean Fuzzy soft-max aggregation operators for healthcare applications[J]. AIMS Mathematics, 2024, 9(3): 6738-6771. doi: 10.3934/math.2024329

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  • The soft-max function, a well-known extension of the logistic function, has been extensively utilized in numerous stochastic classification methodologies, such as linear differential analysis, soft-max extrapolation, naive Bayes detectors, and neural networks. The focus of this study is the development of soft-max based fuzzy aggregation operators (AOs) for Pythagorean fuzzy sets (PyFS), capitalizing on the benefits provided by the soft-max function. In addition to introducing these novel AOs, we also present a comprehensive approach to multi-attribute decision-making (MADM) that employs the proposed operators. To demonstrate the efficacy and applicability of our MADM method, we applied it to a real-world problem involving Pythagorean fuzzy data. The analysis of supplier selection has been extensively examined in many academic works as a crucial component of supply chain management (SCM), recognised as a significant MADM challenge. The process of choosing healthcare suppliers is a pivotal element that has the potential to greatly influence the efficacy and calibre of healthcare provisions. In addition, we given a numerical example to rigorously evaluate the accuracy and dependability of the proposed procedures. This examination demonstrates the effectiveness and potential of our proposed soft-max based AOs and their applicability in Pythagorean fuzzy environments.



    It is with admiration that we share with you our publication data for the 2022 calendar year for the AIMS Medical Science Journal. It was another successful year with the highest number of publication submissions to date over the past three years. Our depth and breadth of publications spanned multiple basic and clinical science disciplines that originated from talented authors across the globe. We look forward to an exciting year ahead and welcome the opportunity to review original manuscripts for consideration for publication in the journal. Our goals are to provide a forum of high-quality manuscripts that can positively impact the expansion of scientific knowledge and advance the health of our population.

    Below is a graphic depiction of the manuscript submission and publication data for the journal for the past three years (Figure 1). There are slightly more submissions that were received in 2022 than in 2021, and the number of accepted and published manuscripts remain stable for the past three years. Our hope is increasing the footprint of quality manuscripts submitted to the journal that will translate into an increased number of high-quality publications for the upcoming year.

    Figure 1.  Manuscript statistics from 2020 to 2022.

    2022 manuscripts status:

    Publications: 28

    Reject rate: 71%

    Publication time (from submission to online): 109 days

    The geographic distribution of the corresponding authors of the published manuscripts are depicted below (Figure 2). We are honored to attract authors from around the world who chose to submit their research to the journal for publication (USA, Canada, Nigeria, Japan, etc.). Of note the majority of publications originate from authors based in the United States representing 39% of the publications followed by Canada and Nigeria standing at 11% each.

    Table 1 depicts the type of manuscripts published. A total of 28 articles were published in 2022, of which, the majority were research based, 12 (43%) followed by reviews, 10 (36%).

    Table 1.  Published articles type.
    Article type Number Percent
    Research article 12 43%
    Review 10 36%
    Others 6 21%
    Total 28

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    Figure 2.  Corresponding authors distribution.

    Table 2 depicts the top 10 articles with the highest views, published in 2022. A focus of these top 10 articles was: Fall Risks, Monoclonal Antibody development and COVID-19.

    Table 2.  The top 10 articles with the highest views, published in 2022.
    Title Corresponding author Views
    1 Knowledge, attitudes on falls and awareness of hospitalized patient's fall risk factors among the nurses working in Tertiary Care Hospitals Surapaneni Krishna Mohan 1861
    2 Clinical pharmacology to support monoclonal antibody drug development Sharon Lu 1861
    3 Telehealth during COVID-19 pandemic era: a systematic review Jonathan Kissi 1787
    4 Understanding the psychological impact of the COVID-19 pandemic on university students Belgüzar Kara 1786
    5 Soluble Fas ligand, soluble Fas receptor, and decoy receptor 3 as disease biomarkers for clinical applications: A review Michiro Muraki 1697
    6 Non-small cell lung cancer: epidemiology, screening, diagnosis, and treatment Anuj A. Shukla 1613
    7 Recurrence after treatment of arteriovenous malformations of the head and neck Nguyen Minh Duc 1583
    8 Staphylococcus aureus antimicrobial efflux pumps and their inhibitors: recent developments Manuel Varela 1467
    9 The mental health of the health care professionals in India during the COVID-19 pandemic: a cross-sectional study B Shivananda Nayak 1268
    10 Recognition, treatment, and prevention of perioperative anaphylaxis: a narrative review Julena Foglia 1210

     | Show Table
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    AIMS Medical Science Journal has 94 members, representing 26 countries. Thirty three percent of the members are from the United States, and other members represent Italy, France, and several other countries (Figure 3). We want to particularly acknowledge our editors: Kelly Pagidas (Editor-in-Chief), Belgüzar Kara, Gulshan Sunavala-Dossabhoy, Gwendolyn Quinn, Panayota Mitrou, Kimberly Udlis (retired), Mai Alzamel, Yi-Jang Lee, Sreekumar Othumpangat, Ji Hyun Kim, Athanasios Alexiou, Robert Striker, Andrei Kelarev, Casey Peiris, Patrick Legembre, Ramin Ataee, Louis Ragolia, Bogdan Borz, Robert Kratzke, Maria Fiorillo, Lars Malmström, Giuliana Banche, Jean-Marie Exbrayat and Elias El-Habr. Importantly, a special thank you to all the Editorial Board members, reviewers and in-house editors, and staff for their dedication, commitment, and unrelenting hard work throughout the year. We hope to attract additional scholars that will be able to join our team for the upcoming year.

    Figure 3.  Editorial board members distribution.


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