khodabakhshi, M., Aryavash, N. (2010). Input congestion, technical ineciency and output reduction in fuzzy data envelopment analysis. Theory of Approximation and Applications, 6(2), 45-60.

M. khodabakhshi; N. Aryavash. "Input congestion, technical ineciency and output reduction in fuzzy data envelopment analysis". Theory of Approximation and Applications, 6, 2, 2010, 45-60.

khodabakhshi, M., Aryavash, N. (2010). 'Input congestion, technical ineciency and output reduction in fuzzy data envelopment analysis', Theory of Approximation and Applications, 6(2), pp. 45-60.

khodabakhshi, M., Aryavash, N. Input congestion, technical ineciency and output reduction in fuzzy data envelopment analysis. Theory of Approximation and Applications, 2010; 6(2): 45-60.

Input congestion, technical ineciency and output reduction in fuzzy data envelopment analysis

^{}Department of Mathematics, Faculty of Science, Lorestan University, Khorram Abad, Iran.

Abstract

During the last years, the concept of input congestion and technical ineff- ciency in data envelopment analysis (DEA), have been investigated by many researchers. The motivation of this paper is to present models which obtain the decreased output value due to input congestion and technical ineciency. More- over, we extend the models to estimate input congestion, technical ineciency and output reduction in fuzzy data envelopment analysis, by using the concept of α-cut sets.

Article Title [Persian]

Input congestion, technical ineciency and output
reduction in fuzzy data envelopment analysis

Authors [Persian]

M. khodabakhshi; N. Aryavash

^{}Department of Mathematics, Faculty of Science, Lorestan University, Khorram Abad, Iran.

Abstract [Persian]

During the last years, the concept of input congestion and technical ineff- ciency in data envelopment analysis (DEA), have been investigated by many researchers. The motivation of this paper is to present models which obtain the decreased output value due to input congestion and technical ineciency. More- over, we extend the models to estimate input congestion, technical ineciency and output reduction in fuzzy data envelopment analysis, by using the concept of α-cut sets.

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