Decision support algorithm under SV-neutrosophic hesitant fuzzy rough information with confidence level aggregation operators

Kamran M., Ismail R., Ashraf S., Salamat N., Yildirim S. O., CANGÜL İ. N.

AIMS Mathematics, cilt.8, sa.5, ss.11973-12008, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 8 Sayı: 5
  • Basım Tarihi: 2023
  • Doi Numarası: 10.3934/math.2023605
  • Dergi Adı: AIMS Mathematics
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Directory of Open Access Journals
  • Sayfa Sayıları: ss.11973-12008
  • Anahtar Kelimeler: aggregation operators, confidence level, decision-making, hesitant information, neutrosophic information, rough sets
  • Bursa Uludağ Üniversitesi Adresli: Evet

Özet

To deal with the uncertainty and ensure the sustainability of the manufacturing industry, we designed a multi criteria decision-making technique based on a list of unique operators for singlevalued neutrosophic hesitant fuzzy rough (SV-NHFR) environments with a high confidence level. We show that, in contrast to the neutrosophic rough average and geometric aggregation operators, which are unable to take into account the level of experts’ familiarity with examined objects for a preliminary evaluation, the neutrosophic average and geometric aggregation operators have a higher level of confidence in the fundamental idea of a more networked composition. A few of the essential qualities of new operators have also been covered. To illustrate the practical application of these operators, we have given an algorithm and a practical example. We have also created a manufacturing business model that takes sustainability into consideration and is based on the neutrosophic rough model. A symmetric comparative analysis is another tool we use to show the feasibility of our proposed enhancements.