Entropy-Based Analysis Using Linear Diophantine Multi Fuzzy Soft Sets: A DEA Approach for Improved Decision Systems
Abstract
This article unveils an innovative approach to improving the entropy measure analysis of Decision Making Units(DMUs) in the context of linear Diophantine multi-fuzzy soft sets. Though multi-fuzzy soft sets combine multi-dimensional values and parameters to create a hybrid model with considerable versatility, linear diophantine fuzzy sets, a noteworthy extension of conventional fuzzy sets, are also utilized to ease prior constraints. Entropy is a fundamental concept in fuzzy set theory and a useful tool for quantifying the level of fuzziness seen in fuzzy sets. We employ entropy measurements to quantify the weights of input and output components in data envelopment analysis, a non-parametric method frequently used in multi-criteria decision-making. The novelty of this study is integrating the weight determination in Data Envelopment Analysis (DEA) by introducing novel entropy measures with linear Diophantine multi-fuzzy soft sets. The significance of DEA is found in its strong analytical capabilities, which facilitate improved decision-making, boost operational effectiveness, and encourage ongoing development in a variety of industries. To illustrate the significance of our suggested approach, we offer a numerical example of building energy efficiency using a DEA model. This work contributes to fuzzy set theory and DEA techniques, offering a helpful tool for evaluating and enhancing complex decision systems.
References
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M. A. Sahil, M. Kaushal, and Q. M. D. Lohani, “A novel pythagorean approach basedsine-shaped fuzzy data envelopment analysis model: An assessment of indian public sectorbanks,”Computational Economics, pp. 1–23, 04 2024. doi: 10.1007/s10614-024-10603-7
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Published
2025-02-04
How to Cite
KANNAN, Jeevitha et al.
Entropy-Based Analysis Using Linear Diophantine Multi Fuzzy Soft Sets: A DEA Approach for Improved Decision Systems.
Yugoslav Journal of Operations Research, [S.l.], feb. 2025.
ISSN 2334-6043.
Available at: <https://yujor.fon.bg.ac.rs/index.php/yujor/article/view/1319>. Date accessed: 11 feb. 2025.
doi: https://doi.org/10.2298/YJOR240315055K.
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Research Articles
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