Your browser doesn't support javascript.
loading
Group decision-making algorithm with sine trigonometric r,s,t-spherical fuzzy aggregation operators and their application.
Azeem, Muhammad; Ilyas, Ayesha; Ali, Jawad; Ghamkhar, Madiha; Syam, Muhammad I.
Affiliation
  • Azeem M; Department of Mathematics and Statistics, University of Agriculture, Faisalabad, 38000, Pakistan.
  • Ilyas A; Department of Mathematics and Statistics, University of Agriculture, Faisalabad, 38000, Pakistan.
  • Ali J; Institute of Numerical Sciences, Kohat University of Science and Technology, Kohat, KPK, Pakistan.
  • Ghamkhar M; Department of Mathematics and Statistics, University of Agriculture, Faisalabad, 38000, Pakistan.
  • Syam MI; Department of Mathematical Sciences, United Arab Emirates University, P. O. Box 15551, Al-Ain, UAE. m.syam@uaeu.ac.ae.
Sci Rep ; 14(1): 10816, 2024 May 11.
Article in En | MEDLINE | ID: mdl-38734743
ABSTRACT
r, s, t-spherical fuzzy (r, s, t-SPF) sets provide a robust framework for managing uncertainties in decision-making, surpassing other fuzzy sets in their ability to accommodate diverse uncertainties through the incorporation of flexible parameters r, s, and t. Considering these characteristics, this article explores sine trigonometric laws to enhance the applicability and theoretical foundation for r, s, t-SPF setting. Following these laws, several aggregation operators (AOs) are designed for aggregation of the r, s, t-SPF data. Meanwhile, the desired characteristics and relationships of these operators are studied under sine trigonometric functions. Furthermore, we build a group decision-making algorithm for addressing multiple attribute group decision-making (MAGDM) problems using the developed AOs. To exemplify the applicability of the proposed algorithm, we address a practical example regarding laptop selection. Finally, parameter analysis and a comprehensive comparison with existing operators are conducted to uncover the superiority and validity of the presented AOs.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Rep Year: 2024 Document type: Article Affiliation country: Pakistan Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Rep Year: 2024 Document type: Article Affiliation country: Pakistan Country of publication: United kingdom