Kazemi Matin, R., Azizi, R. (2015). DEA with Missing Data: An Interval Data Assignment Approach. Journal of Optimization in Industrial Engineering, 8(17), 31-36.
Reza Kazemi Matin; Roza Azizi. "DEA with Missing Data: An Interval Data Assignment Approach". Journal of Optimization in Industrial Engineering, 8, 17, 2015, 31-36.
Kazemi Matin, R., Azizi, R. (2015). 'DEA with Missing Data: An Interval Data Assignment Approach', Journal of Optimization in Industrial Engineering, 8(17), pp. 31-36.
Kazemi Matin, R., Azizi, R. DEA with Missing Data: An Interval Data Assignment Approach. Journal of Optimization in Industrial Engineering, 2015; 8(17): 31-36.
DEA with Missing Data: An Interval Data Assignment Approach
1Associate Professor, Department of Mathematics, Islamic Azad University, Karaj Branch, Karaj, Iran
2MSc, Department of Mathematics, Islamic Azad University, Karaj Branch, Karaj , Iran
Abstract
In the classical data envelopment analysis (DEA) models, inputs and outputs are assumed as known variables, and these models cannot deal with unknown amounts of variables directly. In recent years, there are few researches on handling missing data. This paper suggests a new interval based approach to apply missing data, which is the modified version of Kousmanen (2009) approach. First, the proposed approach suggests using an acceptable range for missing inputs and outputs, which is determined by the decision maker (DM). Then, applying the least favourable bounds of missing data along with using the proposed range is suggested in estimating the production frontier. A data set is used to illustrate the approach.
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