Abstract
This paper proposes a new fuzzy mathematical programming method that was originally proposed to solve problems that can be formulated as LP models using data envelopment analysis (DEA) models and Karush–Kuhn–Tucker (KKT) conditions to evaluate the efficiency of fuzzy systems. KKT condition (also learned as the Kuhn-Tucker condition) is a first derivative trial (whilom called the first-order essential condition) for the optimal nonlinear programming solution. First, the DEA method based on the comparison of \(\alpha \)-cut sets is modeled. Then, applying Karush–Kuhn–Tucker conditions, the model is developed to assess the efficiency of DMUs and \(\alpha \)-levels. The novel produced model results in a new analytical view for the efficiency assessment and also eased the evaluation of a system efficiency condition. The final model is tested on a banking system in the US, over two years and according to this model, the efficiency of DMUs is evaluated. According to the given results, it can be comprehended that the presented method is very accurate and appropriate.
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Acknowledgements
José Francisco Gómez Aguilar acknowledges the support provided by CONACyT: cátedras CONACyT para jóvenes investigadores 2014 and SNI-CONACyT.
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H. Mesgarani: Conceptualization, methodology, validation, formal analysis, investigation; Y. Esmaeelzade Aghdam: Conceptualization, methodology, validation, formal analysis, investigation; A. Beiranvand: Conceptualization, methodology, validation; J.F. Gómez-Aguilar: Conceptualization, methodology, validation, writing-review and editing. All authors have read and agreed to the published version of the manuscript.
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Mesgarani, H., Aghdam, Y.E., Beiranvand, A. et al. A Novel Approach to Fuzzy Based Efficiency Assessment of a Financial System. Comput Econ 63, 1609–1626 (2024). https://doi.org/10.1007/s10614-023-10376-5
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DOI: https://doi.org/10.1007/s10614-023-10376-5