000			02010nab a2200193 4500
005			20260520001039.0
008			260224s2008 xxu
245	0	0	_aData envelopment analysis with uncertain data: An application for Iranian electricity distribution companies
260			_a _b _cnov. 2008
270			_a23/06/2011 ; 23/06/2011
300			_a8 p. ; 4247-4254
520			_aTranscripción del resumen del autor. This paper presents Data Envelopment Analysis (DEA) model with uncertain data for performance assessment of electricity distribution companies. During the past two decades, DEA has been widely used for benchmarking the electricity distribution companies. However, there is no study among many existing DEA approaches where the uncertainty in data is allowed and, at the same time, the distribution of the random data is permitted to be unknown. The proposed method of this paper develops a new DEA method with the consideration of uncertainty on output parameters. The method is based on the adaptation of recently developed robust optimization approaches proposed by Ben-Tal and Nemirovski [2000. Robust solutions of linear programming problems contaminated with uncertain data. Mathematical Programming 88, 411–421] and Bertsimas et al. [2004. Robust linear optimization under general norms. Operations Research Letters 32, 510–516]. The results are compared with an existing parametric Stochastic Frontier Analysis (SFA) using data from 38 electricity distribution companies in Iran to show the effects of the data uncertainties on the performance of DEA outputs. The results indicate that the robust DEA approach can be a relatively more reliable method for efficiency estimating and ranking strategies. Keywords: Data envelopment analysis; Robust optimization; Electricity distribution companies
581			_a11
773	0		_tEnergy Policy _g36
942			_cARTICULO
100	1		_aSadjadi, S.J. _950419
100	1		_aOmrani, H. _940472
999			_c183047 _d183047