Return to Fuzzy DEA

Fuzzy DEA Bibliography

[postlist cat=”alipublications-fuzzy”]

  • Allahviranloo, T., Hosseinzade Lotfi, F., Adabitabar, M. Firozja, 2007. Fuzzy efficiency measure with fuzzy production possibility set. Applications and Applied Mathematics: An International Journal 2 (2), 152–166.
  • Asady, B., Zendehnam, A., 2007. Ranking fuzzy numbers by distance minimization. Applied Mathematical Modelling 11, 2589–2598.
  • Azadeh, A., Alem, S.M., 2010. A flexible deterministic, stochastic and fuzzy data envelopment analysis approach for supply chain risk and vendor selection problem:simulation analysis. Expert Systems with Applications 37 (12), 7438–7448.
  • Azadeh, A., Ghaderi, S.F., Javaheri, Z., Saberi, M., 2008. A fuzzy mathematical programming approach to DEA models. American Journal of Applied Sciences 5 (10), 1352–1357.
  • Azadeh, M.A., Anvari, M., Izadbakhsh, H., 2007. An integrated FDEA–PCA method as decision making model and computer simulation for system optimization. In: Proceedings of the Computer Simulation Conference. Society for Computer Simulation International San Diego, CA, USA, pp. 09–616.
  • Bagherzadeh valami, H., 2009. Cost efficiency with triangular fuzzy number input prices: an application of DEA. Chaos, Solitons and Fractals 42, 1631–1637.
  • Chiang, T.Z., Che, Z.H., 2010. A fuzzy robust evaluation model for selecting and ranking NPD projects using Bayesian belief network and weight-restricted DEA. Expert Systems with Applications 37 (1111), 7408–7418.
  • Dia, M., 2004. A model of fuzzy data envelopment analysis. INFOR 42 (4), 267–279.
  • Entani, T., Maeda, Y., Tanaka, H., 2002. Dual models of interval DEA and its extension to interval data. European Journal of Operational Research 136 (1), 32–45.
  • Garcia, P.A.A., Schirru, R., Melo, P.F.F.E., 2005. A fuzzy data envelopment analysis approach for FMEA. Progress in Nuclear Energy 46 (3–4), 359–373.
  • Ghapanchi, A., Jafarzadeh, M.H., Khakbaz, M.H., 2008. Fuzzy-Data envelopment analysis approach to enterprise resource planning system analysis and selection. International Journal of Information Systems and Change Management 3 (2), 157–170.
  • Girod, O., 1996. Measuring technical efficiency in a fuzzy environment, Ph.D. Dissertation, Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University.
  • Girod, O.A., Triantis, K.P., 1999. The evaluation of productive efficiency using a fuzzy mathematical programming approach: the case of the newspaper preprint insertion process. IEEE Transactions on Engineering Management 46 (4), 429–443.
  • Guh, Y.Y., 2001. Data envelopment analysis in fuzzy environment. International Journal of Information and Management Sciences 12 (2), 51–65.
  • Guo, P., 2009. Fuzzy data envelopment analysis and its application to location problems. Information Sciences 179 (6), 820–829.
  • Guo, P., Tanaka, H., 2001. Fuzzy DEA: a perceptual evaluation method. Fuzzy Sets and Systems 119 (1), 149–160.
  • Guo, P., Tanaka, H., 2008. Decision making based on fuzzy data envelopment analysis, to appear in Intelligent Decision and Policy Making Support Systems. In: Ruan, D., Meer, K. (Eds.). Springer, Berlin/Heidelberg, pp. 39–54.
  • Guo, P., Tanaka, H., Inuiguchi, M., 2000. Self-organizing fuzzy aggregation models to rank the objects with multiple attributes. IEEE Transactions on Systems, Man and Cybernetics, Part A – Systems and Humans 30 (5), 573–580.
  • Hatami-Marbini, A., Saati, S., 2009. Stability of RTS of efficient DMUs in DEA with fuzzy under fuzzy data. Applied Mathematical Sciences 3 (44), 2157–2166.
  • Hatami-Marbini, A., Saati, S., Makui, A., 2009. An application of fuzzy numbers ranking in performance analysis. Journal of Applied Sciences 9 (9), 1770–1775.
  • Hatami-Marbini, A., Saati, S., Makui, A., 2010b. Ideal and anti-ideal decision making units: a fuzzy DEA approach. Journal of Industrial Engineering International 6 (10), 31–41.
  • Hatami-Marbini, A., Saati, S., Tavana, M., 2010a. An ideal-seeking fuzzy data envelopment analysis framework. Applied Soft Computing 10 (4), 1062–1070.
  • Hatami-Marbini, A., Saati, S., Tavana, M., in presse. Data envelopment analysis with fuzzy parameters: an interactive approach. International Journal of Operations Research and Information Systems.
  • Hatami-Marbini, A., Tavana, M., Ebrahimi, A., in pressc. A fully fuzzified data envelopment analysis model. International Journal of Information and Decision Sciences.
  • Hatami-Marbini, A., Tavana, M., Emrouznejad, A., Saati, S., in pressd. Efficiency measurement in fuzzy additive data envelopment analysis. International Journal of Industrial and Systems Engineering.
  • Hosseinzadeh Lotfi, F., Adabitabar Firozja, M., Erfani, V., 2009a. Efficiency measures in data envelopment analysis with fuzzy and ordinal data. International Mathematical Forum 4 (20), 995–1006.
  • Hosseinzadeh Lotfi, F., Allahviranloo, T., Mozaffari, M.R., Gerami, J., 2009b. Basic DEA models in the full fuzzy position. International Mathematical Forum 4 (20), 983–993.
  • Hosseinzadeh Lotfi, F., Jahanshahloo, G.R., Alimardani, M., 2007b. A new approach for efficiency measures by fuzzy linear programming and Application in Insurance Organization. Applied Mathematical Sciences 1 (14), 647–663.
  • Hosseinzadeh Lotfi, F., Jahanshahloo, G.R., Allahviranloo, T., Noroozi, E., Hosseinzadeh Lotfi, A.A., 2007a. Equitable allocation of shared costs on fuzzy environment. International Mathematical Forum 2 (65), 3199–3210.
  • Hosseinzadeh Lotfi, F., Jahanshahloo, G.R., Rezai Balf, F., Zhiani Rezai, H., 2007c. Discriminant analysis of imprecise data. Applied Mathematical Sciences 1 (15), 723–737.
  • Hosseinzadeh Lotfi, F., Jahanshahloo, G.R., Vahidi, A.R., Dalirian, A., 2009c. Efficiency and effectiveness in multi-activity network DEA model with fuzzy data. Applied Mathematical Sciences 3 (52), 2603–2618.
  • Hosseinzadeh Lotfi, F., Mansouri, B., 2008. The extended data envelopment analysis/discriminant analysis approach of fuzzy models. Applied Mathematical Sciences 2 (30), 1465–1477.
  • Hougaard, J.L., 1999. Fuzzy scores of technical efficiency. European Journal of Operational Research 115 (3), 529–541.
  • Hougaard, J.L., 2005. A simple approximation of productivity scores of fuzzy production plans. Fuzzy Sets and Systems 152 (3), 455–465.
  • Hsu, K.H., 2005. Using balanced scorecard and fuzzy data envelopment analysis for multinational R & D project performance assessment. Journal of American Academy of Business, Cambridge 7 (1), 189–196.
  • imposing of weights restrictions. Applied Mathematics and Computation 156 (1), 175–187.
  • Jahanshahloo, G.R., Hosseienzadeh Lotfi, F., Shoja, N., Sanei, M., 2004b. An alternative approach for equitable allocation of shared costs by using DEA. Applied Mathematics and computation 153 (1), 267–274.
  • Jahanshahloo, G.R., Hosseinzade Lotfi, F., Shoja, N., Tohidi, G., Razavian, S., 2004c. Ranking by l1 _ norm in data envelopment analysis. Applied Mathematics and Computation 153 (1), 215–224.
  • Jahanshahloo, G.R., Hosseinzadeh Lotfi, F., Adabitabar Firozja, M., Allahviranloo, T., 2007b. Ranking DMUs with fuzzy data in DEA. International Journal Contemporary Mathematical Sciences 2 (5), 203–211.
  • Jahanshahloo, G.R., Hosseinzadeh Lotfi, F., Alimardani Jondabeh, M., Banihashemi, Sh., Lakzaie, L., 2008. Cost efficiency measurement with certain price on fuzzy data and application in insurance organization. Applied Mathematical Sciences 2 (1), 1–18.
  • Jahanshahloo, G.R., Hosseinzadeh Lotfi, F., Nikoomaram, H., Alimardani, M., 2007a. 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.
  • Jahanshahloo, G.R., Hosseinzadeh Lotfi, F., Shahverdi, R., Adabitabar, M., Rostamy-Malkhalifeh, M., Sohraiee, S., 2009b. Ranking DMUs by l1 _ normwith fuzzy data in DEA. Chaos, Solitons and Fractals 39, 2294–2302.
  • Jahanshahloo, G.R., Sanei, M., Rostamy-Malkhalifeh, M., Saleh, H., 2009a. A comment on a fuzzy DEA/AR approach to the selection of flexible manufacturing systems. Computers and Industrial Engineering 56 (4), 1713–1714.
  • Jahanshahloo, G.R., Soleimani-Damaneh, M., Nasrabadi, E., 2004a. Measure of efficiency in DEA with fuzzy input–output levels: a methodology for assessing, ranking and
  • Jiang, N., Yang, Y., 2007. A fuzzy chance-constrained DEA model based on Cr measure. International Journal of Business and Management 2 (2), 17–21.
  • Jimenez, M., 1996. Ranking fuzzy numbers through the comparison of its expected intervals. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 4 (4), 379–388.
  • Juan, Y.K., 2009. 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.
  • Kahraman, C., Tolga, E. 1998. Data envelopment analysis using fuzzy concept. 28th International Symposium on Multiple-Valued Logic, pp. 338–343.
  • Kao, C., 2001. A mathematical programming approach to fuzzy efficiency ranking. Proceedings of the International Conference on Fuzzy Systems, vol. 1. Institute of Electrical and Electronics Engineers Inc., Melbourne, Australia, pp. 216–219.
  • Kao, C., 2006. Interval efficiency measures in data envelopment analysis with imprecise data. European Journal of Operational Research 174, 1087–1099.
  • Kao, C., Liu, S.T., 2000a. Fuzzy efficiency measures in data envelopment analysis. Fuzzy Sets and Systems 113 (3), 427–437.
  • Kao, C., Liu, S.T., 2000b. Data envelopment analysis with missing data: an application to University libraries in Taiwan. Journal of Operational Research Society 51 (8), 897–905.
  • Kao, C., Liu, S.T., 2003. A mathematical programming approach to fuzzy efficiency ranking. International Journal of Production Economics 86 (2), 145–154.
  • Kao, C., Liu, S.T., 2005. Data envelopment analysis with imprecise data: an application of Taiwan machinery firms. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 13 (2), 225–240.
  • Kao, C., Liu, S.T., 2007. Data envelopment analysis with missing data: a reliable solution method, to appear. In: Zhu, J., Cook, W.D. (Eds.), Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis. Springer, pp. 292–304.
  • Karsak, E.E., 2008. Using data envelopment analysis for evaluating flexible manufacturing systems in the presence of imprecise data. The International Journal of Advanced Manufacturing Technology 35 (9-10), 867–874.
  • Khodabakhshi, M., Gholami, Y., Kheirollahi, H., 2010. An additive model approach for estimating returns to scale in imprecise data envelopment analysis. Applied Mathematical Modelling 34 (5), 1247–1257.
  • Kuo, H.C., Wang, L.H., 2007. Operating performance by the development of efficiency measurement based on fuzzy DEA. Second International Conference on Innovative Computing, Information and Control, p. 196.
  • Lee, H.S., 2004. A fuzzy data envelopment analysis model based on dual program. Conference Proceedings – 27th edition of the Annual German Conference on Artificial Intelligence, pp. 31–39.
  • Lee, H.S., Shen, P.D., Chyr, W.L., 2005. 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), vol. 3682. Springer Verlag, Melbourne, Australia, Heidelberg, Germany, pp. 343–349. D-69121.
  • Leon, T., Liern, V., Ruiz, J.L., Sirvent, I., 2003. A fuzzy mathematical programming approach to the assessment of efficiency with DEA models. Fuzzy Sets and Systems 139 (2), 407–419.
  • Lertworasirikul, S., 2002. Fuzzy Data Envelopment Analysis (DEA), Ph.D. Dissertation, Dept. of Industrial Engineering, North Carolina State University.
  • Lertworasirikul, S., Fang, S.C., Joines, J.A., Nuttle, H.L.W., 2003c. Fuzzy data envelopment analysis (fuzzy DEA): a credibility approach. In: Verdegay, J.L. (Ed.), Fuzzy Sets Based Heuristics for Optimization. Physica Verlag, pp. 141–158.
  • Lertworasirikul, S., Fang, S.C., Joines, J.A., Nuttle, H.L.W., 2003a. Fuzzy data envelopment analysis (DEA): a possibility approach. Fuzzy Sets and Systems 139 (2), 379–394.
  • Lertworasirikul, S., Fang, S.C., Joines, J.A., Nuttle, H.L.W., 2002b. A possibility approach to fuzzy data envelopment analysis. Proceedings of the joint conference on information sciences, vol. 6. Duke University/Association for Intelligent Machinery, Durham, US, pp. 176–179.
  • Lertworasirikul, S., Fang, S.C., Nuttle, H.L.W., Joines, J.A., 2003b. Fuzzy BCC model for data envelopment analysis. Fuzzy Optimization and Decision Making 2 (4), 337–358.
  • Lertworasirikul, S., Fang, S.C., Nuttle, H.L.W., Joines, J.A., 2002a. Fuzzy data envelopment analysis, Proceedings of the 9th Bellman Continuum, Beijing, p. 342.
  • Li, N., Yang, Y., 2008. FDEA-DA: discriminant analysis method for grouping observations with fuzzy data based on DEA-DA. Chinese Control and Decision Conference, art. no. 4597688, pp. 2060–2065.Liu, B., 2004. Uncertainty Theory: An Introduction to its Axiomatic Foundations. Springer-Verlag, Berlin.
  • Liu, S.T., 2008. A fuzzy DEA/AR approach to the selection of flexible manufacturing system. Computer and Industrial Engineering 54, 66–76.
  • Liu, S.T., Chuang, M., 2009. Fuzzy efficiency measures in fuzzy DEA/AR with application to university libraries. Expert Systems with Applications 36 (2), 1105–1113.
  • Liu, Y.P., Gao, X.L., Shen, Z.Y., 2007. Product design schemes evaluation based on fuzzy DEA. Computer Integrated Manufacturing Systems 13 (11), 2099–2104.
  • Luban, F., 2009. Measuring efficiency of a hierarchical organization with fuzzy DEA method. Economia, Seria Management 12 (1), 87–97.
  • Meada, Y., Entani, T., Tanaka, H., 1998. Fuzzy DEA with interval efficiency. Proceedings of 6th European Congress on Intelligent Techniques and Soft Computing. EUFIT ’98. Aachen, Germany, Verlag Mainz. 2, pp. 1067–1071.
  • Molavi, F., Aryanezhad, M.B., Shah Alizadeh, M., 2005. An efficiency measurement model in fuzzy environment, using data envelopment analysis. Journal of Industrial Engineering International 1 (1), 50–58.
  • Noora, A.A., Karami, P., 2008. Ranking functions and its application to fuzzy DEA. International Mathematical Forum 3 (30), 1469–1480.
  • Noura, A.A., Saljooghi, F.H., 2009. Ranking decision making units in fuzzy-DEA using entropy. Applied Mathematical Sciences 3 (6), 287–295.
  • Pal, R., Mitra, J., Pal, M.N., 2007. 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.
  • Qin, R., Liu, Y., Liu, Z., Wang, G., 2009. Modeling fuzzy DEA with type-2 fuzzy variable coefficients. In: Lecture Notes in Computer Science. Springer, Berlin/Heidelberg, pp. 25–34.
  • Qin, R., Liu, Y.K., 2009. A new data envelopment analysis model with fuzzy random inputs and outputs. Journal of Applied Mathematics and Computing. 10.1007/s12190-009-0289-7.
  • Qin, R., Liu, Y.K., 2010. Modeling data envelopment analysis by chance method in hybrid uncertain environments. Mathematics and Computers in Simulation 80 (5), 922–950.
  • Ramezanzadeh, S., Memariani, A., Saati, S., 2005. Data envelopment analysis with fuzzy random inputs and outputs: a chance-constrained programming approach. Iranian Journal of Fuzzy Systems 2 (2), 21–29.
  • Saati, S., Memariani, A., 2005. Reducing weight flexibility in fuzzy DEA. Applied Mathematics and Computation 161 (2), 611–622.
  • Saati, S., Memariani, A., 2006. 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.
  • Saati, S., Memariani, A., 2009. SBM model with fuzzy input–output levels in DEA. Australian Journal of Basic and Applied Sciences 3 (2), 352–357.
  • Saati, S., Memariani, A., Jahanshahloo, G.R., 2002. Efficiency analysis and ranking of DMUs with fuzzy data. Fuzzy Optimization and Decision Making 1, 255–267.
  • Sanei, M., Noori, N., Saleh, H., 2009. Sensitivity analysis with fuzzy Data in DEA. Applied Mathematical Sciences 3 (25), 1235–1241.
  • Saneifard, R., Allahviranloo, T., Hosseinzadeh Lotfi, F., Mikaeilvand, N., 2007. Euclidean ranking DMUs with fuzzy data in DEA. Applied Mathematical Sciences 1 (60), 2989–2998.
  • Seiford, L.M., 1996. Data envelopment analysis: the evolution of the state of the art (1978–1995). The Journal of Productivity Analysis 7, 99–137.
  • Sengupta, J.K., 1992a. A fuzzy systems approach in data envelopment analysis. Computers and Mathematics with Applications 24 (8-9), 259–266.
  • Sengupta, J.K., 1992b. Measuring efficiency by a fuzzy statistical approach. Fuzzy Sets and Systems 46 (1), 73–80.
  • Sheth, N., Triantis, K., 2003. Measuring and evaluating efficiency and effectiveness using goal programming and data envelopment analysis in a fuzzy environment. Yugoslav Journal of Operations Research 13 (1), 35–60.
  • Soleimani-Damaneh, M., 2008. Fuzzy upper bounds and their applications. Chaos, Solitons and Fractals 36, 217–225.
  • Soleimani-damaneh, M., 2009. Establishing the existence of a distance-based upper bound for a fuzzy DEA model using duality. Chaos, Solitons and Fractals 41, 485–490.
  • Soleimani-damaneh, M., Jahanshahloo, G.R., Abbasbandy, S., 2006. Computational and theoretical pitfalls in some current performance measurement techniques and a new approach. Applied Mathematics and Computation 181 (2), 1199–1207.
  • Sueyoshi, T., 1999. DEA-discriminant analysis in the view of goal programming. European Journal of Operational Research 115, 564–582.
  • Sueyoshi, T., 2001. Extended DEA-discriminant analysis. European Journal of Operational Research 131, 324–351.
  • Tlig, H., Rebai, A., 2009. A mathematical approach to solve data envelopment analysis models when data are LR fuzzy numbers. Applied Mathematical Sciences 3 (48), 2383–2396.
  • Triantis, K., 2003. Fuzzy non-radial data envelopment analysis (DEA) measures of technical efficiency in support of an integrated performance measurement system. International Journal of Automotive Technology and Management 3 (3-4), 328–353.
  • Triantis, K.P., Girod, O., 1998. A mathematical programming approach for measuring technical efficiency in a fuzzy environment. Journal of Productivity Analysis 10 (1), 85–102.
  • Uemura, Y., 2006. Fuzzy satisfactory evaluation method for covering the ability comparison in the context of DEA efficiency. Control and Cybernetics 35 (2), 487–495.
  • Wang, C.H., Chuang, C.C., Tsai, C.C., 2009b. A fuzzy DEA–neural approach to measuring design service performance in PCM projects. Automation in Construction 18, 702–713.
  • Wang, Y.M., Greatbanks, R., Yang, J.B., 2005. Interval efficiency assessment using data envelopment analysis. Fuzzy Sets and Systems 153 (3), 347–370.
  • Wang, Y.M., Luo, Y., Liang, L., 2009a. Fuzzy data envelopment analysis based upon fuzzy arithmetic with an application to performance assessment of manufacturing enterprises. Expert Systems with Applications 36, 5205–5211.
  • Wen, M., Li, H., 2009. Fuzzy data envelopment analysis (DEA): model and ranking method. Journal of Computational and Applied Mathematics 223, 872–878.
  • Wen, M., You, C., Kang, R., 2010. A new ranking method to fuzzy data envelopment analysis. Computers & Mathematics with Applications 59 (11), 3398–3404.
  • Wu, D., Yang, Z., Liang, L., 2006. Efficiency analysis of cross-region bank branches using fuzzy data envelopment analysis. Applied Mathematics and Computation 181, 271–281.
  • Wu, R., Yong, J., Zhang, Z., Liu, L., Dai, K., 2005. A game model for selection of purchasing bids in consideration of fuzzy values. Proceedings of the international conference on services systems and services management, vol. 1. IEEE, New York, pp. 254–258.
  • Zerafat Angiz, L.M., Emrouznejad, A., Mustafa, A., 2010a. Fuzzy assessment of performance of a decision making units using DEA: a non-radial approach. Expert Systems with Applications 37 (7), 5153–5157.
  • Zerafat Angiz, L.M., Emrouznejad, A., Mustafa, A., al-Eraqi, A.S., 2010b. Aggregating preference ranking with fuzzy data envelopment analysis. Knowledge-Based Systems 23 (6), 512–519.
  • Zerafat Angiz, L.M., Saati, S., Memariani, M.A., Movahedi, M., 2006. Solving possibilistic linear programming problem considering membership function of the coefficients. Advances in Fuzzy Sets and Systems 1 (2), 131–142.
  • Zhang, L., Mannino, M., Ghosh, B., Scott, J., 2005. Data warehouse (DWH) efficiency evaluation using fuzzy data envelopment analysis (FDEA). Proceedings of the Americas Conference on Information Systems 113, 1427–1436.
  • Zhou, S.J., Zhang, Z.D., Li, Y.C., 2008. 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, pp. 444–448.