[1] Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management science, 39(10), 1261-1264.
[2] 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.
[3] Duckstein, L. (1995). Fuzzy rule-based modeling with applications to geophysical, biological, and engineering systems (Vol. 8). CRC press.
[4] Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444.
[5] Cooper, W. W., Park, K. S., & Yu, G. (1999). IDEA and AR-IDEA: models for dealing with imprecise data in DEA. Management science, 45(4), 597-607.
[6] Delgado, M., Vila, M. A., & Voxman, W. (1998). On a canonical representation of fuzzy numbers. Fuzzy sets and systems, 93(1), 125-135.
[7] DuboisandH, D. (1988). Prade, possibility theory: an approach to computerized processing of uncertainty. New York, NY, USA: Plenum.
[8] Goetschel Jr, R., & Voxman, W. (1986). Elementary fuzzy calculus. Fuzzy sets and systems, 18(1), 31-43.
[9] Jahanshahloo. G. R., Hosseinzadeh Lotfi. F., Shahverdi, R., Adabitabar, M., Rostamy-Malkhalifeh, M., & Sohraiee, S. (2009) .Ranking DMUs by -norm with fuzzy data in DEA. Chaos, solitons and fractals, 39, 2294–2302.
[10] Jahanshahloo, G. R., Lotfi, F. H., Shoja, N., Tohidi, G., & Razavyan, S. (2004). Ranking using l1-norm in data envelopment analysis. Applied mathematics and computation, 153(1), 215-224.
[11] Kao, C., & Liu, S. T. (2000). Fuzzy efficiency measures in data envelopment analysis. Fuzzy sets and systems, 113(3), 427-437.
[12] Mehrabian, S., Alirezaee, M. R., & Jahanshahloo, G. R. (1999). A complete efficiency ranking of decision making units in data envelopment analysis. Computational optimization and applications, 14(2), 261-266.
[13] Balf, F. R., Rezai, H. Z., Jahanshahloo, G. R., & Lotfi, F. H. (2012). Ranking efficient DMUs using the Tchebycheff norm. Applied mathematical modelling, 36(1), 46-56.
[14] Seaver, B. L., & Triantis, K. P. (1992). A fuzzy clustering approach used in evaluating technical efficiency measures in manufacturing. Journal of productivity analysis, 3(4), 337-363.
[15] Seiford, L. M., & Zhu, J. (1999). Infeasibility of super-efficiency data envelopment analysis models. INFOR: information systems and operational research, 37(2), 174-187.
[16] Sengupta, J. K. (1992). A fuzzy systems approach in data envelopment analysis. Computers & mathematics with applications, 24(8-9), 259-266.
[17] Tavares, G., & Antunes, C. H. (2001). A Tchebycheff DEA model. Working Paper, Rutgers University, 640 Bartholomew Road, Piscataway, NJ 08854-8003.
[18] Tran, L., & Duckstein, L. (2002). Comparison of fuzzy numbers using a fuzzy distance measure. Fuzzy sets and systems, 130(3), 331-341.
[19] Yao, J. S., & Wu, K. (2000). Ranking fuzzy numbers based on decomposition principle and signed distance. Fuzzy sets and systems, 116(2), 275-288.
[20] Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353.