Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092.
 Bazaraa, M. S., Sherali, H. D., & Shetty, C. M. (2013). Nonlinear programming: theory and algorithms. John Wiley & Sons.
 Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444.
 Cochocki, A., & Unbehauen, R. (1993). Neural networks for optimization and signal processing. John Wiley & Sons, Inc..
 Cooper, W. W., Seiford, L. M., & Tone, K. (2006). Introduction to data envelopment analysis and its uses: with DEA-solver software and references. Springer Science & Business Media.
 Kinderlehrer, D., & Stampacchia, G. (1980). An introduction to variational inequalities and their applications (Vol. 31). Siam.
 Xia, Y., & Wang, J. (1998). A general methodology for designing globally convergent optimization neural networks. Neural Networks, IEEE Transactions on, 9(6), 1331-1343.
 Xia, Y., & Wang, J. (2000). A recurrent neural network for solving linear projection equations. Neural Networks, 13(3), 337-350.
 Xia, Y., Leung, H., & Wang, J. (2002). A projection neural network and its application to constrained optimization problems. Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on, 49(4), 447-458.
 Zabczyk, J. (2009). Mathematical control theory: an introduction. Springer Science & Business Media.