Affiliations: Department of Mathematics, Yadegar-e-Imam Khomeini (RAH) Shahre Rey Branch, Islamic Azad University, Tehran, Iran
Correspondence:
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Corresponding author. Mahnaz Mirbolouki, Department of Mathematics, Yadegar-e-Imam Khomeini (RAH) Shahre Rey Branch, Islamic Azad University, Tehran, Iran. E-mail: [email protected].
Abstract: In classical models of data envelopment analysis, the identification of factors as input or output factors has been assumed. In the last decade, research on the impact of flexible factors on the assessment of the efficiency of decision-making units has been expanded. Flexible factors are factors that cannot be categorized precisely as input or output factors. In this paper, unlike former studies, the classification of fuzzy flexible measures is addressed. Here, two kinds of absolute and fuzzy classifications are introduced for fuzzy flexible factors. In fact, the proposed classifier fuzzy models, unlike the absolute input/output classifications in former models, is such that part of the flexible measures can play input role for all DMUs and the rest are treated as output. The advantage of a fuzzy classification is the ability to make a unique decision on defining the type of each flexible measure. This feature prevents an inhomogeneous status of decision making units.
Keywords: Data envelopment analysis, input and output factors, flexible measures, fuzzy numbers
