A taxonomy and review of the fuzzy DEA literature: Two decades

Hatami-Marbini, A., A. Emrouznejad and M. Tavana (2011). 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. https://doi.org/10.1016/j.ejor.2011.02.001 

 

 

List of papers on A taxonomy and review of the fuzzy Data Envelopment Analysis literature: Two decades in the making:

  • 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.
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  • Cook, W.D., Kress, M., Seiford, L.M., 1996. Data envelopment analysis in the presence of both quantitative and qualitative factors. Journal of Operational Research Society 47, 945–953.
  • Cook, W.D., Seiford, L.M., 2009. Data envelopment analysis (DEA) – Thirty years on. European Journal of Operational Research 192 (1), 1–17.
  • Cooper, W.W., Deng, H., Huang, Z.M., Li, S.X., 1996. Satisfying DEA models under chance constraints. The Annals of Operations Research 66, 279–295.
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  • Emrouznejad, A., Parker, B.R., Tavares, G., 2008. Evaluation of research in efficiency and productivity: a survey and analysis of the first 30 years of scholarly literature in DEA. Socio-Economic Planning Sciences 42 (3), 151–157.
  • 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.
  • Figueira, J., Greco, S., Ehrgott, M. (Eds.), 2004. Multiple Criteria Decision Analysis: State of the Art Surveys. Springer, New York.
  • 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.
  • Gattoufi, S., Oral, M., Reisman, A., 2004. A taxonomy for data envelopment analysis. Socio-Economic Planning Sciences 38 (2–3), 141–158.
  • Geldermann, J., Spengler, T., Rentz, O., 2000. Fuzzy outranking for environmental assessment. Case study: Iron and steel making industry. Fuzzy Sets and Systems 115 (1), 45–65.
  • 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.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.
  • 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.
  • Guh, Y.Y., 2001. Data envelopment analysis in fuzzy environment. International Journal of Information and Management Sciences 12 (2), 51–65.
  • 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., 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., 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., Tavana, M., 2010a. An ideal-seeking fuzzy data envelopment analysis framework. Applied Soft Computing 10 (4), 1062–1070.
  • 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., 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.
  • 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.
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  • 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., 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., 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., 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.
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  • 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.
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  • 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 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., 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., Adabitabar Firozja, M., Allahviranloo, T., 2007b. Ranking DMUs with fuzzy data in DEA. International Journal Contemporary Mathematical Sciences 2 (5), 203–211.
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