Atanassov, K. T. (1999). Intuitionistic fuzzy sets. In Intuitionistic fuzzy sets (pp. 1-137). Physica, Heidelberg.
Chen, N., Xu, Z., & Xia, M. (2013). Interval-valued hesitant preference relations and their applications to group decision making. Knowledge-based systems, 37, 528-540.
Deli, I. (2020). A TOPSIS method by using generalized trapezoidal hesitant fuzzy numbers and application to a robot selection problem. Journal of intelligent & fuzzy systems, 38(1), 779-793.
Denoeux, T. (2014). Dempster-Shafer theory, introduction, connections with rough sets and application to
Feng, L., Chuan-qiang, F., & Wei-he, X. (2018). Type-2 hesitant fuzzy sets. Fuzzy information and engineering, 10(2), 249-259.
Garg, H., Arora, R. (2020). TOPSIS method based on correlation coefficient for solving decision-making problems with intuitionistic fuzzy soft set information. AIMS mathematics, 5(4), 2944-2966.
Garg, H., Keikha, A., & Mishmast Nehi, H. (2020). Multiple-attribute decision-making problem using TOPSIS and choquet integral with hesitant fuzzy number information.
Mathematical problems in engineering,
2020.
https://doi.org/10.1155/2020/9874951
Hu, J., Xiao, K., Chen, X., & Liu, Y. (2015). Interval type-2 hesitant fuzzy set and its application in multi-criteria decision making. Computers & industrial engineering, 87, 91-103.
Jafari, H., & Ehsanifar, M. (2020). Using interval arithmetic for providing a MADM approach. Journal of fuzzy extension and applications, 1(1), 57-65.
Jin, F., Ni, Z., & Chen, H. (2016). Interval-valued hesitant fuzzy Einstein prioritized aggregation operators and their applications to multi-attribute group decision making. Soft computing, 20(5), 1863-1878.
Joshi, D., & Kumar, S. (2016). Interval-valued intuitionistic hesitant fuzzy Choquet integral based TOPSIS method for multi-criteria group decision making. European journal of operational research, 248(1), 183-191.
Kayedppour, F., Sayadmanesh, Sh., Salmani, Y., & Sadeghi, Z. (2020). Measuring the efficiency and productivity of cement companies in Tehran Stock Exchange by data envelopment analysis and Malmquist productivity index in gray environment.
Innovation management and operational strategies, 1(4), 363-382. (
In Persian).
https://www.sid.ir/fa/Journal/ViewPaper.aspx?ID=554606
Keikha, A. (2015).
Fuzzy Choquet integral and its application in multi-attribute decision making (Ph.D. Thesis,
University of Sistan and Baluchestan). (
In Persian).
Keikha, A. (2021). Introducing a new type of HFSs and their application in solving MADM.
Journal of intelligence & fuzzy systems, 40(4),
1-12. DOI:
10.3233/JIFS-201808
Keikha, A., & Mishmast Nehi, H. (2021). Introducing a new model for evaluating and ranking employees, organizations and solving MADM problems in a hesitant fuzzy environment. Journal of decisions and operations research, 6(2), 256-270. (In Persian). DOI: 10.22105/dmor.2021.238906.1177
Klir, G. J. (2006). Uncertainty and information: foundations of generalized information theory. John Wiley & Sons.
Kumar, A., Kaur, J., & Singh, P. (2011). A new method for solving fully fuzzy linear programming problems. Applied mathematical modelling, 35(2), 817-823.
Lalotra, S., & Singh, S. (2020). Knowledge measure of hesitant fuzzy set and its application in multi-attribute decision-making. Computational and applied mathematics, 39(2), 1-31.
Liao, H., & Xu, Z. (2013). A VIKOR-based method for hesitant fuzzy multi-criteria decision making. Fuzzy optimization and decision making, 12(4), 373-392.
Liao, H., & Xu, Z. (2014a). Subtraction and division operations over hesitant fuzzy sets. Journal of intelligent & fuzzy systems, 27(1), 65-72.
Liao, H., & Xu, Z. (2014b). Some new hybrid weighted aggregation operators under hesitant fuzzy multi-criteria decision making environment. Journal of intelligent & fuzzy systems, 26(4), 1601-1617.
Liao, H., & Xu, Z. (2017). Hesitant fuzzy decision making methodologies and applications. Springer Singapore.
Liao, H., Wu, X., Keikha, A., & Hafezalkotob, A. (2018). Power average-based score function and extension rule of hesitant fuzzy set and the hesitant power average operators. Journal of intelligent & fuzzy systems, 35(3), 3873-3882.
Maghsoudi, E., Shirouyehzad, H., & Shahin, A. (2015). Prioritization and analysis agility factors affecting the performance of project based organizations with Topsis technique. Journal of applied research on industrial engineering, 2(3), 195-203.
Mansory, A., Nasiri, A., & Mohammadi, N. (2021). Proposing an integrated model for evaluation of green and resilient suppliers by path analysis, SWARA and TOPSIS. Journal of applied research on industrial engineering, 8(2), 129-149.
Meng, F., Wang, C., & Chen, X. (2016). Linguistic interval hesitant fuzzy sets and their application in decision making. Cognitive computation, 8(1), 52-68.
Palczewski, K., & Sałabun, W. (2019). The fuzzy TOPSIS applications in the last decade. Procedia computer science, 159, 2294-2303.
Pollack, H. N. (2005). Uncertain science... uncertain world. Cambridge University Press.
Qiaoping, S. U. N., & Ouyang, J. (2015). Hesitant fuzzy multi-attribute decision making based on TOPSIS with entropy-weighted method. Management science and engineering, 9(3), 1-6.
Ranjbar, M., Miri, S. M., & Effati, S. (2020). Hesitant fuzzy numbers with (α, k)-cuts in compact intervals and applications.
Expert systems with applications,
151, 113363.
https://doi.org/10.1016/j.eswa.2020.113363
Rouhbakhsh, F. F., Ranjbar, M., Effati, S., & Hassanpour, H. (2020). Multi objective programming problem in the hesitant fuzzy environment. Applied intelligence, 50(10), 2991-3006.
Salicone, S. (2007). Measurement uncertainty: an approach via the mathematical theory of evidence. Springer Science & Business Media.
Smithson, M. (1988). Ignorance and uncertainty. Springer.
Tong, X., & Yu, L. (2016). MADM based on distance and correlation coefficient measures with decision-maker preferences under a hesitant fuzzy environment. Soft computing, 20(11), 4449-4461.
Torra, V. (2010). Hesitant fuzzy sets. International journal of intelligent systems, 25(6), 529-539.
Torra, V., & Narukawa, Y. (2009, August). On hesitant fuzzy sets and decision. 2009 IEEE international conference on fuzzy systems (pp. 1378-1382). IEEE.
Tzeng, G. H., & Huang, J. J. (2011). Multiple attribute decision making: methods and applications. CRC press.
Wang, X., & Triantaphyllou, E. (2008). Ranking irregularities when evaluating alternatives by using some ELECTRE methods. Omega, 36(1), 45-63.
Wei, G. (2012). Hesitant fuzzy prioritized operators and their application to multiple attribute decision making. Knowledge-based systems, 31, 176-182.
Wei, G., Alsaadi, F. E., Hayat, T., & Alsaedi, A. (2016). Hesitant fuzzy linguistic arithmetic aggregation operators in multiple attribute decision making. Iranian journal of fuzzy systems, 13(4), 1-16.
Wei, G., Wang, H., Zhao, X., & Lin, R. (2014). Approaches to hesitant fuzzy multiple attribute decision making with incomplete weight information. Journal of intelligent & fuzzy systems, 26(1), 259-266.
Wei, G., Zhao, X., Wang, H., & Lin, R. (2012). Hesitant fuzzy choquet integral aggregation operators and their applications to multiple attribute decision making. International information institute (Tokyo), 15(2), 441-448.
Xia, M., & Xu, Z. (2011a). Hesitant fuzzy information aggregation in decision making. International journal of approximate reasoning, 52(3), 395-407.
Xia, M., & Xu, Z. (2011b). Methods for fuzzy complementary preference relations based on multiplicative consistency. Computers & industrial engineering, 61(4), 930-935.
Xu, Z., & Xia, M. (2011). Distance and similarity measures for hesitant fuzzy sets. Information Sciences, 181(11), 2128-2138.
Xu, Z., & Xia, M. (2012). Hesitant fuzzy entropy and cross‐entropy and their use in multiattribute decision‐making. International journal of intelligent systems, 27(9), 799-822.
Yu, D., Wu, Y., & Zhou, W. (2011). Multi-criteria decision making based on choquet integral under hesitant fuzzy environment. Journal of computational information systems, 7(12), 4506–4513.
Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353.
Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning—I. Information sciences, 8(3), 199-249.
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