1] Mehregan, M .(2004). Quantitative models in evaluating organizations performance (DEA). Chapter 2 and 3, Tehran University Press Faculty Publishing.
 Ajalli, M., & Safari, H. (2011). Analysis of the Technical Efficiency of the Decision Making Units Making Use of the Synthetic Model of Performance Predictor Neural Networks, and Data Envelopment Analysis (Case Study: Gas National Co. Of Iran), Journal of Industrial Engineering Vol, 45, No.1.
 Rezaeian, J., & Asgarinezhad, A. (2014). Performance Evaluation of Mazandaran Water and Wastewater by Data Envelopment Analysis and Artificial Neural Network, Journal of Industrial Engineering Vol, 48, No.2.
 Toloie-Eshlaghy, A., Alborzi, M., & Ghafari, B. (2012). Assessment of the personnel’s efficiency with Neuro/DEA combined model. Elixir Mgmt. Arts Vol. 43, No.1. PP.6605-6617.
 Shokrollahpour, E., Lotfi, F. H., & Zandieh, M. (2016). An integrated data envelopment analysis–artificial neural network approach for benchmarking of bank branches. Journal of Industrial Engineering International, 12(2), 137-143.
 Çelen, A. (2013). Efficiency and productivity (TFP) of the Turkish electricity distribution companies: An application of two-stage (DEA&Tobit) analysis. Energy Policy, 63, 300-310.
 Wu, Y., Hu, Y., Xiao, X., & Mao, C. (2016). Efficiency assessment of wind farms in China using two-stage data envelopment analysis. Energy Conversion and Management, 123, 46-55.
 Hjalmarsson, L., & Veiderpass, A. (1992). Efficiency and ownership in Swedish electricity retail distribution. International Applications of Productivity and Efficiency Analysis (pp. 3-19): Springer.
 Bagdadioglu, N., Price, C. M. W., & Weyman-Jones, T. G. (1996). Efficiency and ownership in electricity distribution: a non-parametric model of the Turkish experience. Energy Economics, 18(1-2), 1-23.
 Pérez-Reyes, R., & Tovar, B. (2009). Measuring efficiency and productivity change (PTF) in the Peruvian electricity distribution companies after reforms. Energy Policy, 37(6), 2249-2261.
 Hattori, T., Jamasb, T., & Pollitt, M. G. (2003). A comparison of UK and Japanese electricity distribution performance 1985-1998: lessons for incentive regulation.
 Hess, B., & Cullmann, A. (2007). Efficiency analysis of East and West German electricity distribution companies–Do the “Ossis” really beat the “Wessis”? Utilities Policy, 15(3), 206-214.
 Goto, M., & Tsutsui, M. (2008). Technical efficiency and impacts of deregulation: An analysis of three functions in US electric power utilities during the period from 1992 through 2000. Energy Economics, 30(1), 15-38.
 Bongo, M. F., Ocampo, L. A., Magallano, Y. A. D., Manaban, G. A., & Ramos, E. K. F. (2018). Input–output performance efficiency measurement of an electricity distribution utility using super-efficiency data envelopment analysis. Soft Computing. doi:10.1007/s00500-018-3007-2
 Meibodi, A. E. (1998). Efficiency considerations in the electricity supply industry: The case of Iran .Chapter 1, university of Surrey.
 Sadjadi, S., & Omrani, H. (2008). Data envelopment analysis with uncertain data: An application for Iranian electricity distribution companies. Energy Policy, 36(11), 4247-4254.
 Fallahi, M., & Ahmadi, V. (2005). Cost efficiency analysis of electricity distribution companies in Iran. Journal of Economic Researches, 71, 297-320.
 Russell, R. R. (1985). Measures of technical efficiency. Journal of Economic Theory, 35(1), 109-126.
 Charnes, A., Cooper, W., Lewin, A., & Seiford, L. (1995). Data Envelopment Analysis: Theory, Methodology and Applications, Kluwer Publications.
 Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 130(3), 498-509.
 Tobin, J. (1958). Estimation of Relationships for Limited Dependent Variables. Econometrica, 26(1), 24-36.
 Olatubi, W. and Dismukes D. (2000), “A Data Envelopment Analysis of the Levels and Determinants of Coal-fired Electric Power Generation Performance”, Utilities Policy, 9, PP. 47–59.
 Dreyfus, G. (2005). Neural networks: methodology and applications: Springer Science & Business Media.
 Alborzi, Mahmood. (2014). Translated of neural computing: an introduction-R Beale & T Jackson. Chapter 4, Institute of Scientific Publications of Sharif University of Technology: Tehran.
 Athanassopoulos, A. D., & Curram, S. P. (1996). A Comparison of Data Envelopment Analysis and Artificial Neural Networks as Tools for Assessing the Efficiency of Decision Making Units. Journal of the Operational Research Society, 47(8), 1000-1016.
 Costa, Á., & Markellos, R. N. (1997). Evaluating public transport efficiency with neural network models. Transportation Research Part C: Emerging Technologies, 5(5), 301-312.
 Wu, D. D., Yang, Z., & Liang, L. (2006). Using DEA-neural network approach to evaluate branch efficiency of a large Canadian bank. Expert systems with applications, 31(1), 108-115.
 Samoilenko, S., & Osei-Bryson, K.-M. (2010). Determining sources of relative inefficiency in heterogeneous samples: Methodology using Cluster Analysis, DEA and Neural Networks. European Journal of Operational Research, 206(2), 479-487.
 Alborzi, Mahmood. (2014). Genetic algorithm. Chapter 3-5, Institute of Scientific Publications of Sharif University of Technology: Tehran.
 Angeline, P. J. (1998). Using selection to improve particle swarm optimization. Paper presented at the Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on.
 Garg, H. (2016). A hybrid PSO-GA algorithm for constrained optimization problems. Applied Mathematics and Computation, 274, 292-305.
 Toloie Ashlaghi, A, Afshar Kazemi, M.A. And Abbasi, F. (2013) Evaluation of the performance of insurance companies based on a balanced scorecard card and data envelopment analysis technique and providing a development path for inefficient companies. Journal of Business Management (17), 65-82.
 Azar, A. Daneshvar, M. Khodadad Hosseiny, S. H. Azizi, S.(2012). Designing a multilevel performance evaluation model: A robust data envelopment analysis approach. Enterprise Resource Management Research, Volume II (3), 1-22.
 Cook WD and Green RH.( 2005). Evaluating power company efficiency: a hierarchical model. Computers & Operations Research; 32: 813-823.