A robust super-efficiency data envelopment analysis model for ranking of provincial gas companies in Iran

Authors:
S. J. Sadjadi;H. Omrani;S. Abdollahzadeh;M. Alinaghian;H. Mohammadi
Affiliations:
Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran;Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran and Department of Industrial Engineering, Urmia University of Technology, Orumiyeh, Iran;Department of Industrial Engineering, Urmia University of Technology, Orumiyeh, Iran;Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran;Qom Gas Company, Qom, Iran
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

Conventional super-efficiency data envelopment analysis (DEA) models require the exact information of inputs or outputs. However, in many real world applications this simple assumption does not hold. Stochastic super-efficiency is one of recent methods which could handle uncertainty in data. Stochastic super-efficiency DEA models are normally formulated based on chance constraint programming. The method is used to estimate the efficiency of various decision making units (DMUs). In stochastic chance constraint super-efficiency DEA, the distinction of probability distribution function for input/output data is difficult and also, in several cases, there is not enough data for estimating of distribution function. We present a new method which incorporates the robust counterpart of super-efficiency DEA. The perturbation and uncertainty in data is assumed as ellipsoidal set and the robust super-efficiency DEA model is extended. The implementation of the proposed method of this paper is applied for ranking different gas companies in Iran.