___

• [1] Adlera, N., Friedman, L., Sinuany-Stern, Z., Review of ranking methods in the data envelopment analysis context, European Journal of Operational Research, 140, 249-265, 2002.
• [2] Bagherzadeh Valami, H., Cost efficiency with triangular fuzzy number input prices: An application of DEA, Chaos, Solitons and Fractals, 42, 1631-1637, 2009.
• [3] Banker, R. D., Thrall, R. M., Estimation of returns to scale using Data Envelopment Analysis, European Journal of Operational Research, 62, 74-84, 1992.
• [4] Bellman, R. E., Zadeh, L. A., Decision-making in a fuzzy environment, Management Science, 17, 141-164, 1970.
• [5] Budak, H., Erpolat, S., Interval data envelopment analysis and an applıcation in turkish banking sector, European Scientific Journal May, 9(13), 36-50, 2013.
• [6] Charnes, A., Clark, T., Cooper, W. W., & Rhodes, E., Measuring the efficiency of decision-making units, European Journal of Operational Research, 2, 429-444, 1978.
• [7] Charnes, A., Cooper, W. W., Golany, B., Seiford, L., Stutz, V. A., Foundations of data envelopment analysis for Pareto-Koopman efficient empirical production frontiers, Journal of Econometrics, 30, 91-107, 1985.
• [8] Chen, C. B., Klein, C. M., An efficient approach to solving fuzzy MADM problems, Fuzzy Sets and Systems, 88, 51-67, 1997a.
• [9] Chen, C. B., Klein, C. M., A simple approach to ranking a group of aggregated fuzzy utilities, IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics, 27, 26-35, 1997b.
• [10] Dia, M., A model of fuzzy data envelopment analysis, INFOR, 42(4), 267-279, 2004.
• [11] Dubois, D., Prade H., Fuzzy Sets and System: Theory and Application, Academic Press, New York, 1980.
• [12] Goetschel, R., Voxman, W., Elementary Fuzzy calculus, Fuzzy Sets and Systems 18, 31-43, 1986.
• [13] Guo, P., Fuzzy data envelopment analysis and its application to locatio problems, Information Sciences, 179(6), 820-829, 2009.
• [14] Guo P., Tanaka H., Decision making based on fuzzy data envelopment analysis, to appear in Intelligent Decision and Policy Making Support Systems (Ruan D. and K. Meer, Eds.) Springer Berlin / Heidelberg, 39-54, 2008.
• [15] Guo, P., Tanaka H., Fuzzy DEA: A perceptual evaluation method, Fuzzy Sets and Systems, 119(1), 149-160, 2001.
• [16] Hatami-Marbini, A., Saati, S., Tavana, M., An ideal-seeking fuzzy data envelopment analysis framework, Applied Soft Computing, 10(4), 1062-1070, 2010a.
• [17] Hatami-Marbini, A., Saati, S., Makui, A., Ideal and anti-Ideal decision making units: A fuzzy DEA approach, Journal of Industrial Engineering International, 6(10), 31-41, 2010b.
• [18] Hatami-Marbini, A., Saati, S., Tavana, M., Data envelopment analysis with fuzzy parameters: An interactive approach, International Journal of Operations Research and Information Systems, 2(3), 39-53, 2011.
• [19] Hatami-Marbini, A., Tavana, M., Ebrahimi, A., A fully fuzzified data envelopment analysis model, International Journal of Information and Decision Sciences, 3(3), 252-264, 2011.
• [20] Hatami-Marbini, A., Saati, S., Stability of RTS of efficient DMUs in DEA with fuzzy under fuzzy data, Applied Mathematical Sciences, 3(44), 2157-2166, 2009.
• [21] Hatami-Marbini, A., Emrouznejad, A., Tavana, M., A Taxonomy and Review of the Fuzzy Data Envelopment Analysis Literature: Two Decades in the Making, European Journal of Operational Research, 214(3), 457-472, 2011.
• [22] Hosseinzadeh Lotfi, F., Jahanshahloo, G. R., Alimardani, M., A new approach for efficiency measures by fuzzy linear programming and Application in Insurance Organization, Applied Mathematical Sciences, 1(14), 647-663, 2007b.
• [23] Hosseinzadeh Lotfi, F., Mansouri, B., The extended data envelopment analysis/Discriminant analysis approach of fuzzy models, Applied Mathematical Sciences, 2(30), 1465-1477, 2008.
• [24] Hosseinzadeh Lotfi, F., Adabitabar Firozja, M., Erfani, V., Efficiency measures in data envelopment analysis with fuzzy and ordinal data, International Mathematical Forum, 4(20), 995-1006, 2009a.
• [25] Hosseinzadeh Lotfi, F., Allahviranloo T., Mozaffari M. R., Gerami J., Basic DEA models in the full fuzzy position, International Mathematical Forum, 4(20), 983-993, 2009b.
• [26] Hosseinzadeh Lotfi, F., Jahanshahloo G. R., Vahidi A. R., Dalirian A., Efficiency and effectiveness in multi-activity network DEA model with fuzzy data, Applied Mathematical Sciences, 3(52), 2603-2618, 2009c.
• [27] Jahanshahloo, G. R., Soleimani-Damaneh, M., Nasrabadi, E., Measure of efficiency in DEA with fuzzy input-output levels: A methodology for assessing, ranking and imposing of weights restrictions, Applied Mathematics and Computation, 156(1), 175-187, 2004a.
• [28] Jahanshahloo, G. R., Hosseienzadeh Lotfi, F., Shoja, N., Sanei, M., An alternative approach for equitable allocation of shared costs by using DEA, Applied Mathematics and computation, 153(1), 267-274, 2004b.
• [29] Jahanshahloo, G. R., Hosseinzade Lotfi, F., Shoja, N., Tohidi, G., Razavian, S., Ranking by ?1norm in data envelopment analaysis, Applied Mathematics and Computation, 153(1), 215-224, 2004c.
• [30] Jahanshahloo, G. R., Hosseinzadeh Lotfi, F., Shahverdi, R., Adabitabar M., Rostam Malkhalifeh M., Sohraiee S., Ranking DMUs by DEA, Chaos, Solitons and Fractals, 39, 2294-2302, 2009b.
• [31] Jahanshahloo G. R., Hosseinzadeh Lotfi F., Alimardani Jondabeh M., Banihashemi Sh., Lakz aie L., Cost efficiency measurement with certain price on fuzzy data and application in insurance organization, Applied Mathematical Sciences, 2(1), 1-18, 2008.
• [32] Jahanshahloo, G. R., Hosseinzadeh Lotfi, F., Nikoomaram, H., Alimardani, M., Using a certain linear ranking function to measure the Malmquist productivity index with fuzzy data and application in insurance organization, Applied Mathematical Sciences, 1(14), 665-680, 2007a.
• [33] Jahanshahloo, G. R., Hosseinzadeh Lotfi, F., Adabitabar Firozja, M., Allahviranloo, T., Ranking DMUs with Fuzzy Data in DEA, International Journal Contemporary Mathematical Sciences, 2(5), 203-211, 2007b.
• [34] Juan, Y. K., A hybrid approach using data envelopment analysis and case-based reasoning for housing refurbishment contractors selection and performance improvement, Expert Systems with Applications, 36(3), 5702-5710, 2009.
• [35] Kauffman, A., Gupta, M. M., Introduction to Fuzzy Arithmetic: Theory and Application, Van Nostrand Reinhold, New York, 1991.
• [36] Kao, C., Liu, S. T., Fuzzy efficiency measures in data envelopment analysis, Fuzzy Set System, 113(3), 427-437, 2000.
• [37] Kao, C., Liu, S. T., A mathematical programming approach to fuzzy efficiency ranking, International Journal of Production Economics, 86, 145-154, 2003.
• [38] Lee, H. S., A fuzzy data envelopment analysis model based on dual program, Conference Proceedings-27th edition of the Annual German Conference on Artificial Intelligence, 31-39, 2004.
• [39] Lee, H. S., Shen, P. D., Chyr, W. L., A fuzzy method for measuring efficiency under fuzzy environment. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Melbourne, Australia, Springer Verlag, Heidelberg, D-69121, Germany, 3682, 343-349, 2005.
• [40] Leon, T., Liern, V., Ruiz, J. L., Sirvent, I., A fuzzy mathematical programming approach to the assessment of efficiency with DEA models, Fuzzy Sets and Systems, 139(2), 407-419, 2003.
• [41] Lertworasirikul, S., Fang, S. C., Joines, J. A., Nuttle, H. L. W., Fuzzy data envelopment analysis (DEA): a possibility approach, Fuzzy Set System, 139(2), 379-394, 2003.
• [42] Lertworasirikul, S., Fang, S. C., Nuttle, H. L. W., Joines, J. A., Fuzzy BCC model for data envelopment analysis, Fuzzy Optimization and Decision Making, 2(4), 337-358, 2003.
• [43] Liu, Y. P., Gao, X. L., Shen, Z. Y., Product design schemes evaluation based on fuzzy DEA, Computer Integrated Manufacturing Systems, 13(11), 2099-2104, 2007.
• [44] Ma, M., Friedman, M., Kandel, A., A new fuzzy arithmetic, Fuzzy Sets and Systems, 108, 83-90, 1999.
• [45] Majid Zerafat Angiz, L., Mustafa, A., Emrouznejad, A., Ranking efficient decision-making units in data envelopment analysis using fuzzy concept, Computers & Industrial Engineering, 8(59), 712-719, 2010.
• [46] Moore, R. E., Kearfott, R. B., Cloud, M. J., Introduction to interval analysis, SIAM, Philadelphia, 2009.
• [47] Molavi, F., Aryanezhad, M. B., Shah Alizade, M., An efficiency measurement model in fuzzy environment, using data envelopment analysis, Journal of Industrial Engineering International, 1(1), 50-58, 2005.
• [48] Noora, A. A., Karami, P., Ranking functions and its application to fuzzy DEA, International Mathematical Forum, 3(30), 1469-1480, 2008.
• [49] Oruç, K. O., Güngör, D., Comparıson of Fuzzy Data Envelopment Analysis Models: For Interval Data, Journal of Faculty of Economics and Administrative Sciences, 15(2), 417-442, 2010.
• [50] Pal, R., Mitra, J., Pal, M. N., Evaluation of relative performance of product designs: a fuzzy DEA approach to quality function deployment, Journal of the Operations Research Society of India, 44(4), 322-336, 2007.
• [51] Razavi, S. H., Amoozad, H., Zavadskas, E. K., Hashemi, S. S., A Fuzzy Data Envelopment Analysis Approach based on Parametric Programming, Int. J. Comput. Commun., 8(4), 594-607, 2013.
• [52] Saati, S., Memariani, A., Jahanshahloo, G. R., Efficiency analysis and ranking of DMUs with fuzzy data, Fuzzy Optimization and Decision Making, 1, 255-267, 2002.
• [53] Saati, S., Memariani, A., A note on "Measure of efficiency in DEA with fuzzy input- output levels: A methodology for assessing, ranking and imposing of weights restrictions" by Jahanshahloo et al, Journal of Science, Islamic Azad University, 16(58/2), 15-18, 2006.
• [54] Saati, S., Memariani, A., Reducing weight flexibility in fuzzy DEA, Applied Mathematics and Computation, 161(2), 611-622, 2005.
• [55] Saati, S., Memariani, A., SBM model with fuzzy input-output levels in DEA, Australian Journal of Basic and Applied Sciences, 3(2), 352-357, 2009.
• [56] Sanei, M., Noori, N., Saleh, H., Sensitivity analysis with fuzzy Data in DEA, Applied Mathematical Sciences, 3(25), 1235-1241, 2009.
• [57] Soleimani-Damaneh, M., Fuzzy upper bounds and their applications, Chaos, Solitons and Fractals, 36, 217-225, 2008.
• [58] Soleimani-Damaneh, M., Jahanshahloo, G. R., Abbasbandy, S., Computational and theoretical pitfalls in some current performance measurement techniques and a new approach, Applied Mathematics and Computation, 181(2), 1199-1207, 2006.
• [59] Wang, C. H., Chuang, C. C, Tsai, C. C., A fuzzy DEA–Neural approach to measuring design service performance in PCM projects, Automation in Construction, 18, 702-713, 2009b.
• [60] Wang X., Kerre, E. E., Reasonable properties for the ordering of fuzzy quantities (I), Fuzzy Sets and Systems, 118, 375-385, 2001.
• [61] Yao, J., Wu, K., Ranking fuzzy numbers based on decomposition principle and signed distance, Fuzzy Sets and Systems, 116, 275-288, 2000.
• [62] Ying-Ming, W., Richard, G., Jian-Bo, Y., Interval efficiency using data envelopment analysis, Fuzzy Sets and Systems, 153, 347-370, 2005.
• [63] Zadeh, L. A., Fuzzy sets, Information and Control, 8, 338-353, 1965.
• [64] Zhou, S. J., Zhang, Z. D., Li, Y. C., Research of real estate investment risk evaluation based on fuzzy data envelopment analysis method, Proceedings of the International Conference on Risk Management and Engineering Management, 444-448, 2008.
• [65] Zimmermann, H. J., Fuzzy Set Theory and Its Applications Kluwer, Dordrecht, 1991