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  • Nov 13, 2024 | mdpi.com | Huizhe Wang |Bo Wang |Yiheng Wang |Qiang Deng

    All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.

  • Sep 19, 2024 | mdpi.com | Qiang Deng

    1. IntroductionData Envelopment Analysis (DEA) is a prominent method for assessing the efficiency of decision-making units (DMUs) [1]. Critical to its success is the selection of appropriate inputs and outputs, a task that poses significant challenges for decision-makers, particularly in stochastic environments where data uncertainties can significantly affect efficiency estimates [2,3]. Despite DEA’s widespread adoption, variable-selection methods often fall short.

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