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SI, AMALENDU, Das, Sujit. (1404). MFS: Dynamic decision making approach to select optimal alternative in the presence of uncertainty. نشریه علمی دانشگاه سیستان و بلوچستان, 22(2), 81-95. doi: 10.22111/ijfs.2025.49694.8773
AMALENDU SI; Sujit Das. "MFS: Dynamic decision making approach to select optimal alternative in the presence of uncertainty". نشریه علمی دانشگاه سیستان و بلوچستان, 22, 2, 1404, 81-95. doi: 10.22111/ijfs.2025.49694.8773
SI, AMALENDU, Das, Sujit. (1404). 'MFS: Dynamic decision making approach to select optimal alternative in the presence of uncertainty', نشریه علمی دانشگاه سیستان و بلوچستان, 22(2), pp. 81-95. doi: 10.22111/ijfs.2025.49694.8773
SI, AMALENDU, Das, Sujit. MFS: Dynamic decision making approach to select optimal alternative in the presence of uncertainty. نشریه علمی دانشگاه سیستان و بلوچستان, 1404; 22(2): 81-95. doi: 10.22111/ijfs.2025.49694.8773

MFS: Dynamic decision making approach to select optimal alternative in the presence of uncertainty

Iranian Journal of Fuzzy Systems
دوره 22، شماره 2، خرداد و تیر 2025، صفحه 81-95    اصل مقاله (831.12 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22111/ijfs.2025.49694.8773
نویسندگان
AMALENDU SI* 1؛ Sujit Das2
1Maulana Abul Kalam Azad University of Technology
2Quarter No D 4/4, Nit Warangal Staff Quarter (Outside Campus)
چکیده
The concept of a multi-fuzzy set (MFS) is a hybrid mathematical approach
that aids reasoning and decision-making in situations characterized by impre
cise information and multiple occurrences. Researchers have developed robust
MFS-based frameworks that facilitate decision-making by identifying optimal
alternatives. However, these frameworks often struggle to select the desired alter
native in uncommon situations. To address the limitations of existing methods,
we incorporated relations and operators with MFS to better measure levels of
uncertainty. To enhance the effectiveness of decision-making, we proposed two
approaches based on the significance of the criteria within the MFS framework.
First, we introduced a relative weight-based approach, where the weight of each
criterion is estimated dynamically. Second, we developed a normalized-based
decision-making approach, which generates optimal solutions based on normal
ized score factors. We demonstrated the effectiveness of our proposed approaches
using semi-realistic cases in health science and healthcare management. Further
more, we evaluated the performance of the healthcare system across different
socio-economic regions, which helped to illustrate the relative importance of the
criteria
کلیدواژه‌ها
Multi-fuzzy set؛ Pivot point؛ Pivot degree؛ Score factor؛ Healthcare system
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