ADLER, N., FRIEDMAN, L. & SINUANY-STERN, Z. 2002. Review of ranking methods in the data envelopment analysis context. European journal of operational research, 140, 249-265.
AMIRI, M., ZANDIEH, M., VAHDANI, B., SOLTANI, R. & ROSHANAEI, V. 2010. An integrated eigenvector–DEA–TOPSIS methodology for portfolio risk evaluation in the FOREX spot market. Expert Systems with Applications, 37, 509-516.
ANDERSEN, P. & PETERSEN, N. C. 1993. A procedure for ranking efficient units in data envelopment analysis. Management science, 39, 1261-1264.
ARYA, A. & YADAV, S. P. 2019. Development of intuitionistic fuzzy data envelopment analysis models and intuitionistic fuzzy input–output targets. Soft Computing, 23, 8975-8993.
ATANASSOV, K. T. 1986. Intuitionistic fuzzy sets. Fuzzy sets and Systems, 20, 87-96.
ATANASSOV, K. T. 1989. More on intuitionistic fuzzy sets. Fuzzy sets and systems, 33, 37-45.
ATANASSOV, K. T. 1999. Intuitionistic fuzzy sets, Springer.
BANKER, R. D., CHARNES, A. & COOPER, W. W. 1984. Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30, 1078-1092.
BORUJENI, M. P. & GITINAVARD, H. 2017. Evaluating the sustainable mining contractor selection problems: An imprecise last aggregation preference selection index method. Journal of Sustainable Mining, 16, 207-218.
BUSTINCE, H. & BURILLO, P. 1996. Vague sets are intuitionistic fuzzy sets. Fuzzy Sets and Systems, 79, 403-405.
CHARNES, A., COOPER, W. W. & RHODES, E. 1978. Measuring the efficiency of decision making units. European journal of operational research, 2, 429-444.
CHEN, N. & XU, Z. 2015. Hesitant fuzzy ELECTRE II approach: A new way to handle multi-criteria decision making problems. Information Sciences, 292, 175-197.
CHEN, T.-Y. 2014. An ELECTRE-based outranking method for multiple criteria group decision making using interval type-2 fuzzy sets. Information Sciences, 263, 1-21.
DANESHVAR ROUYENDEGH, B. 2011. The DEA and intuitionistic fuzzy TOPSIS approach to departments' performances: a pilot study. Journal of Applied Mathematics, 2011.
DAVOUDABADI, R., MOUSAVI, S.M., MOHAGHEGHI, V., 2020. A new last aggregation method of multi-attributes group decision making based on concepts of TODIM, WASPAS and TOPSIS under interval-valued intuitionistic fuzzy uncertainty, Knowledge and Information Systems, 62, 1371–1391.
DU, Y. & LIU, P. 2011. Extended fuzzy VIKOR method with intuitionistic trapezoidal fuzzy numbers. Information-An International Interdisciplinary Journal, 14, 2575-2583.
EBRAHIMNEJAD, S., MOUSAVI, S., TAVAKKOLI-MOGHADDAM, R., HASHEMI, H. & VAHDANI, B. 2012. A novel two-phase group decision making approach for construction project selection in a fuzzy environment. Applied Mathematical Modelling, 36, 4197-4217.
GAU, W.-L. & BUEHRER, D. J. 1993. Vague sets. IEEE transactions on systems, man, and cybernetics, 23, 610-614.
GHADERI, H., BABAZADEH, R., MOINI, A. & PISHVAEE, M. S. 2019. Efficiency assessment of switchgrass cultivation areas using sustainable indicators under epistemic uncertainty. Computers and electronics in agriculture, 157, 12-22.
GHADERI, H., GITINAVARD, H., MOUSAVI, S. M. & VAHDANI, B. 2017. A hesitant fuzzy cognitive mapping approach with risk preferences for student accommodation problems. International Journal of Applied Management Science, 9, 253-293.
GITINAVARD, H. & AKBARPOUR SHIRAZI, M. 2018. An extended intuitionistic fuzzy modified group complex proportional assessment approach. Journal of Industrial and Systems Engineering, 11, 229-246.
GITINAVARD, H., GHADERI, H. & PISHVAEE, M. S. 2018. Green supplier evaluation in manufacturing systems: a novel interval-valued hesitant fuzzy group outranking approach. Soft Computing, 22, 6441-6460.
GITINAVARD, H., MOUSAVI, S. M. & VAHDANI, B. 2017. Soft computing based on hierarchical evaluation approach and criteria interdependencies for energy decision-making problems: A case study. Energy, 118, 556-577.
GITINAVARD, H. & ZARANDI, M. H. F. 2016. A mixed expert evaluation system and dynamic interval-valued hesitant fuzzy selection approach. International Journal of Mathematical, Computational, Physical, Electrical and Computer Engineering, 10, 337-345.
HAJIAGHA, S. H. R., AKRAMI, H., ZAVADSKAS, E. K. & HASHEMI, S. S. 2013. An intuitionistic fuzzy data envelopment analysis for efficiency evaluation under uncertainty: case of a finance and credit institution. E&M Ekonomie a Management, 16, 128-137.
HAJIGHASEMI, Z., MOUSAVI, S.M., 2018. A new approach in failure modes and effects analysis based on compromise solution by considering objective and subjective weights with interval-valued intuitionistic fuzzy sets, Iranian Journal of Fuzzy Systems, 15(1), 2018, 139-161.
LIM, S., OH, K. W. & ZHU, J. 2014. Use of DEA cross-efficiency evaluation in portfolio selection: An application to Korean stock market. European Journal of Operational Research, 236, 361-368.
LIU, J., SONG, J., XU, Q., TAO, Z. & CHEN, H. 2019. Group decision making based on DEA cross-efficiency with intuitionistic fuzzy preference relations. Fuzzy Optimization and Decision Making, 18, 345-370.
MA, R., YAO, L., JIN, M. & REN, P. 2014. The DEA Game Cross-efficiency Model for Supplier Selection Problem under Competition. Appl. Math, 8, 811-818.
MANSOURI, A., EBRAHIMI, N. & RAMAZANI, M. 2014. Ranking of Companies Considering TOPSIS-DEA Approach Methods (Evidence from Cement Industry in Tehran Stock Exchange). Pakistan Journal of Statistics & Operation Research, 10.
MENG, D. & PEI, Z. 2013. On weighted unbalanced linguistic aggregation operators in group decision making. Information Sciences, 223, 31-41.
MOUSAVI, S. M. & VAHDANI, B. 2016. Cross-docking location selection in distribution systems: a new intuitionistic fuzzy hierarchical decision model. International Journal of computational intelligence Systems, 9, 91-109.
MOUSAVI, S. M., VAHDANI, B. & BEHZADI, S. S. 2016. Designing a model of intuitionistic fuzzy VIKOR in multi-attribute group decision-making problems. Iranian Journal of Fuzzy Systems, 13, 45-65.
MOUSAVI, S.M., ANTUCHEVIČIENĖ, J., ZAVADSKAS, E. K., VAHDANI, B., HASHEMI, H., 2019. A new decision model for cross-docking center location in logistics networks under interval-valued intuitionistic fuzzy uncertainty, Transport, 34(1), 30-40.
OTAY, İ., OZTAYSI, B., ONAR, S. C. & KAHRAMAN, C. 2017. Multi-expert performance evaluation of healthcare institutions using an integrated intuitionistic fuzzy AHP&DEA methodology. Knowledge-Based Systems, 133, 90-106.
QIN, J. & LIU, X. 2015. Multi-attribute group decision making using combined ranking value under interval type-2 fuzzy environment. Information Sciences, 297, 293-315.
SZMIDT, E. & KACPRZYK, J. 2000. Distances between intuitionistic fuzzy sets. Fuzzy sets and systems, 114, 505-518.
TOLOO, M. 2015. Alternative minimax model for finding the most efficient unit in data envelopment analysis. Computers & Industrial Engineering, 81, 186-194.
VAHDANI, B., MOUSAVI, S. M., TAVAKKOLI-MOGHADDAM, R. & HASHEMI, H. 2013. A new design of the elimination and choice translating reality method for multi-criteria group decision-making in an intuitionistic fuzzy environment. Applied Mathematical Modelling, 37, 1781-1799.
WEI, G., ZHAO, X. & LIN, R. 2010. Some induced aggregating operators with fuzzy number intuitionistic fuzzy information and their applications to group decision making. International Journal of Computational Intelligence Systems, 3, 84-95.
WU, H., YANG, J., CHEN, Y., LIANG, L. & CHEN, Y. 2019a. DEA-based production planning considering production stability. INFOR: Information Systems and Operational Research, 57, 477-494.
WU, P., WANG, Y., CHIU, Y.-H., LI, Y. & LIN, T.-Y. 2019b. Production efficiency and geographical location of Chinese coal enterprises-undesirable EBM DEA. Resources Policy, 64, 101527.
XIA, P., WU, J., JI, X. & XI, P. 2020. A DEA-based empirical analysis for dynamic performance of China's regional coke production chain. Science of The Total Environment, 717, 136890.
XU, Z.-S. & CHEN, J. 2007. An interactive method for fuzzy multiple attribute group decision making. Information Sciences, 177, 248-263.
XU, Z. 2007. Intuitionistic fuzzy aggregation operators. Fuzzy Systems, IEEE Transactions on, 15, 1179-1187.
XU, Z. 2010. A deviation-based approach to intuitionistic fuzzy multiple attribute group decision making. Group Decision and Negotiation, 19, 57-76.
XU, Z. & YAGER, R. R. 2006. Some geometric aggregation operators based on intuitionistic fuzzy sets. International journal of general systems, 35, 417-433.
YUE, Z. 2014. TOPSIS-based group decision-making methodology in intuitionistic fuzzy setting. Information Sciences, 277, 141-153.
ZADEH, L. 1965. Fuzzy set theory and its applications. Kluwer-Nijhoff, Boston.
ZHANG, X. & LIU, P. 2010. Method for aggregating triangular fuzzy intuitionistic fuzzy information and its application to decision making. Technological and economic development of economy, 280-290.
ZHANG, X. & XU, Z. 2014. Interval programming method for hesitant fuzzy multi-attribute group decision making with incomplete preference over alternatives. Computers & Industrial Engineering, 75, 217-229
SALARPOUR, H., GHODRATI AMIRI, G., & MOUSAVI, S.M., 2019. Criteria assessment in sustainable macromanagement of housing provision problem by a multi-phase decision approach with DEMATEL and dynamic uncertainty, Arabian Journal for Science and Engineering 44, 7313–733.