Entropy-based analysis using linear diophantine multi fuzzy soft sets: A DEA approach for improved decision systems
DOI:
https://doi.org/10.2298/YJOR240315055KKeywords:
Linear diophantine multi-fuzzy soft set, entropy measure, DEA, energy efficiencyAbstract
This article unveils an innovative approach to improving the entropy measure analysis of Decision Making Units(DMUs) in the context of linear Diophantine multifuzzy 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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