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Article type: Research Article
Authors: Chen, Yubinga; b | Wen, Meilina; b | Wang, Feic; *
Affiliations: [a] Science and Technology on Reliability and Environmental Engineering Laboratory, Beijing, China | [b] School of Reliability and Systems Engineering, Beihang University, Beijing, China | [c] Research Institute of Frontier Science, Beihang University, Beijing, China
Correspondence: [*] Corresponding author. Fei Wang, Research Institute of Frontier Science, Beihang University, Beijing, 100191, China. E-mail: [email protected].
Abstract: Data envelopment analysis (DEA) has become an accepted tool for assessing efficiency in a wide range of cases since it was first proposed in 1978. However, traditional DEA models need accurate inputs and outputs, which can’t be obtained or measured in many practical cases. This paper will apply DEA into uncertain environment, and propose a new DEA model with uncertain inputs and outputs based on uncertain theory. Furthermore, the uncertainty theory is utilized to convert the new uncertain DEA model into an equivalent deterministic model for simplification. Finally, this new uncertain DEA model is applied to the evaluation of scientific research personnel to illustrate the effectiveness.
Keywords: Data envelopment analysis, uncertainty theory, uncertain variable, uncertainty distribution, efficiency
DOI: 10.3233/JIFS-190784
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5633-5640, 2019
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