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A generalized fuzzy DEA/AR performance assessment model
Data envelopment analysis (DEA) is a non-parametric approach for performance assessment of a set of homogeneous decision making units (DMUs), which use similar inputs to produce similar outputs. Crisp data are commonly used in traditional DEA models. However, inputs and outputs have been observed wh...
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Published in: | Mathematical and computer modelling 2012-06, Vol.55 (11-12), p.2117-2128 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Data envelopment analysis (DEA) is a non-parametric approach for performance assessment of a set of homogeneous decision making units (DMUs), which use similar inputs to produce similar outputs. Crisp data are commonly used in traditional DEA models. However, inputs and outputs have been observed whose values are imprecise in many cases. Meanwhile, the weights of inputs and outputs must be maintained in some ranges for the production mechanisms to work in reality. In this paper, a generalized fuzzy DEA model with assurance regions (GFDEA/AR) is proposed. Two linear programming models to determine the lower and upper bounds of fuzzy efficiency scores under given α levels is proposed. The proposed GFDEA/AR model is then used to evaluate the performance of manufacturing enterprises in different cases. |
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ISSN: | 0895-7177 1872-9479 |
DOI: | 10.1016/j.mcm.2012.01.017 |