Hesitant triangular fuzzy FlowSort method: the multi-criteria decision-making problems

References

• Alaa, M., Albakri, I. S. M. A., Singh, C. K. S., Hammed, H., Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., Salih, M. M., Almahdi, E. M., & Baqer, M. J. (2019). Assessment and ranking framework for the English skills of pre-service teachers based on fuzzy Delphi and TOPSIS methods. IEEE Access, 7, 126201–126223. https://doi.org/10.1109/ACCESS.2019.2936898
   Web of Science ®Google Scholar
• Atanassov, K. T. (2016). Studies in fuzziness and soft computing. International Journal of Bioautomation, 20, S1–S6. https://doi.org/10.1007/978-3-7908-1870-3_1
   Google Scholar
• Brans, J. P., & Mareschal, B. (1992). PROMETHEE V: MCDM problems with segmentation constraints. INFOR: Information Systems and Operational Research, 30(2), 85–96. https://doi.org/10.1080/03155986.1992.11732186
   Web of Science ®Google Scholar
• Brans, J. P., & Vincke, P. (1985). Note – a preference ranking organisation method. Management Science, 31(6), 647–656. https://doi.org/10.1287/mnsc.31.6.647
   Web of Science ®Google Scholar
• Brans, J. P., Vincke, P., & Mareschal, B. (1986). How to select and how to rank projects: The PROMETHEE method. European Journal of Operational Research, 24(2), 228–238. https://doi.org/10.1016/0377-2217(86)90044-5
   Web of Science ®Google Scholar
• Bruinsma, M. (2004). Motivation, cognitive processing and achievement in higher education. Learning and Instruction, 14(6), 549–568. https://doi.org/10.1016/j.learninstruc.2004.09.001
   Web of Science ®Google Scholar
• Budak, A., & Ustundag, A. (2015). Fuzzy decision making model for selection of real time location systems. Applied Soft Computing, 36, 177–184. https://doi.org/10.1016/j.asoc.2015.05.057
   Web of Science ®Google Scholar
• Campos, A. C. S. M., Mareschal, B., & de Almeida, A. T. (2015). Fuzzy FlowSort: An integration of the FlowSort method and fuzzy set theory for decision making on the basis of inaccurate quantitative data. Information Sciences, 293, 115–124. https://doi.org/10.1016/j.ins.2014.09.024
   Web of Science ®Google Scholar
• Cant, M. A., Manser, M. B., & Kingdom, U. (2013). Testing for vocal individual discrimination in adult banded mongooses. Journal of Zoology, 1–16.
   Web of Science ®Google Scholar
• Carter, H., Dubois, D., & Prade, H. (1982). Fuzzy sets and systems – theory and applications. Journal of the Operational Research Society, 33(2), 198. https://doi.org/10.1057/jors.1982.39
   Google Scholar
• Chen, J. F., Hsieh, H. N., & Do, Q. H. (2015). Evaluating teaching performance based on fuzzy AHP and comprehensive evaluation approach. Applied Soft Computing, 28, 100–108. https://doi.org/10.1016/j.asoc.2014.11.050
   Web of Science ®Google Scholar
• Chien, T. K. (2007). Using the learning satisfaction improving model to enhance the teaching quality. Quality Assurance in Education, 15(2), 192–214. https://doi.org/10.1108/09684880710748947
   Google Scholar
• Crooks, T. J. (1988). The impact of classroom evaluation practices on students. Review of Educational Research, 58(4), 438. https://doi.org/10.3102/00346543058004438
   Web of Science ®Google Scholar
• Dong, J. Y., Chen, Y., & Wan, S. P. (2018). A cosine similarity based QUALIFLEX approach with hesitant fuzzy linguistic term sets for financial performance evaluation. Applied Soft Computing, 69, 316–329. https://doi.org/10.1016/j.asoc.2018.04.053
   Web of Science ®Google Scholar
• Ďurišová, M., Kucharčíková, A., & Tokarčíková, E. (2015). Assessment of higher education teaching outcomes (quality of higher education). Procedia - Social and Behavioral Sciences, 174, 2497–2502. https://doi.org/10.1016/j.sbspro.2015.01.922
   Google Scholar
• Gaertner, H. (2014). Effects of student feedback as a method of self-evaluating the quality of teaching. Studies in Educational Evaluation, 42, 91–99. https://doi.org/10.1016/j.stueduc.2014.04.003
   Web of Science ®Google Scholar
• 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. https://doi.org/10.1016/S0165-0114(99)00021-4
   Web of Science ®Google Scholar
• Goumas, M., & Lygerou, V. (2000). An extension of the PROMETHEE method for decision making in fuzzy environment: Ranking of alternative energy exploitation projects. European Journal of Operational Research, 123(3), 606–613. https://doi.org/10.1016/S0377-2217(99)00093-4
   Web of Science ®Google Scholar
• Harland, T., Raja Hussain, R. M., & Bakar, A. A. (2014). The scholarship of teaching and learning: Challenges for Malaysian academics. Teaching in Higher Education, 19(1), 38–48. https://doi.org/10.1080/13562517.2013.827654
   Web of Science ®Google Scholar
• Isa, S. G., Mammam, M. A., Badar, Y., & Bala, T. (2020). The impact of teaching methods on academic performance of secondary school students in Nigeria. International Journal of Development Research, 10(7), 37382–37385.
   Google Scholar
• Jiménez Tovar, M., Acevedo-Chedid, J., Ospina-Mateus, H., Salas-Navarro, K., & Sana, S. S. (2023). An optimization algorithm for the multi-objective flexible fuzzy job shop environment with partial flexibility based on adaptive teaching–learning considering fuzzy processing times. Soft Computing, https://doi.org/10.1007/s00500-023-08342-2
   Web of Science ®Google Scholar
• Khaleghi, E., Solatanzadeh, H., & Gholizadeh, M. (2022). Recognition of gait disorder in people with knee joint disability using FUZZY system. Journal of Machine Vision and Image Processing, 9(2), 33–45. [Online]. Available: http://jmvip.sinaweb.net/article_139030.html.
   Google Scholar
• Krishankumar, R., Pamucar, D., Pandey, A., Kar, S., & Ravichandran, K. S. (2022). Double hierarchy hesitant fuzzy linguistic information based framework for personalized ranking of sustainable suppliers. Environmental Science and Pollution Research, https://doi.org/10.1007/s11356-022-20359-y
   Web of Science ®Google Scholar
• Krishankumar, R., Ravichandran, K. S., Kar, S., Gupta, P., & Mehlawat, M. K. (2021). Double-hierarchy hesitant fuzzy linguistic term set-based decision framework for multi-attribute group decision-making. Soft Computing, 25(4), 2665–2685. https://doi.org/10.1007/s00500-020-05328-2
   Web of Science ®Google Scholar
• Krishankumar, R., Ravichandran, K. S., Liu, P., Kar, S., & Gandomi, A. H. (2021). A decision framework under probabilistic hesitant fuzzy environment with probability estimation for multi-criteria decision making. Neural Computing and Applications, 33(14), 8417–8433. https://doi.org/10.1007/s00521-020-05595-y
   Web of Science ®Google Scholar
• 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. https://doi.org/10.1007/s10700-013-9162-0
   Web of Science ®Google Scholar
• Liao, H., Xu, Z., & Zeng, X.-J. (2014). Distance and similarity measures for hesitant fuzzy linguistic term sets and their application in multi-criteria decision making. Information Sciences, 271, 125–142. https://doi.org/10.1016/j.ins.2014.02.125
   Web of Science ®Google Scholar
• Lin, M., Wang, H., & Xu, Z. (2020). TODIM-based multi-criteria decision-making method with hesitant fuzzy linguistic term sets. Artificial Intelligence Review, 53(5), 3647–3671. https://doi.org/10.1007/s10462-019-09774-9
   Web of Science ®Google Scholar
• Liu, D., Liu, Y., & Chen, X. (2018). The new similarity measure and distance measure of a hesitant fuzzy linguistic term set based on a linguistic scale function. Symmetry, 10(9), 367. https://doi.org/10.3390/sym10090367
   Google Scholar
• Liu, H., & Rodríguez, R. M. (2014). A fuzzy envelope for hesitant fuzzy linguistic term set and its application to multicriteria decision making. Information Sciences, 258, 220–238. https://doi.org/10.1016/j.ins.2013.07.027
   Web of Science ®Google Scholar
• Lo, A., & Howard, K. M. (2009). Mobilizing respect and politeness in classrooms. Linguistics and Education, 20(3), 211–216. https://doi.org/10.1016/j.linged.2009.07.001
   Google Scholar
• Miyamoto, S. (2005). Remarks on basics of fuzzy sets and fuzzy multisets. Fuzzy Sets and Systems, 156(3), 427–431. https://doi.org/10.1016/j.fss.2005.05.040
   Web of Science ®Google Scholar
• Moheimani, A., Sheikh, R., Hosseini, S. M. H., & Sana, S. S. (2021). Assessing the agility of hospitals in disaster management: Application of interval type-2 fuzzy FlowSort inference system. Soft Computing, 25(5), 3955–3974. https://doi.org/10.1007/s00500-020-05418-1
   Web of Science ®Google Scholar
• Nemery, P., & Lamboray, C. (2008). Flow sort: A flow-based sorting method with limiting or central profiles. Top, 16(1), 90–113. https://doi.org/10.1007/s11750-007-0036-x
   Web of Science ®Google Scholar
• Osiro, L., Lima-Junior, F. R., & Carpinetti, L. C. R. (2018). A group decision model based on quality function deployment and hesitant fuzzy for selecting supply chain sustainability metrics. Journal of Cleaner Production, 183, 964–978. https://doi.org/10.1016/j.jclepro.2018.02.197
   Web of Science ®Google Scholar
• Palmer, W. (2003). Simple, surprising, useful? Three questions for judging teaching methods. Pedagogy, 3(2), 285–287. https://doi.org/10.1215/15314200-3-2-285
   Google Scholar
• Pedrycz, W., & Song, M. (2011). Analytic hierarchy process (AHP) in group decision making and its optimization with an allocation of information granularity. IEEE Transactions on Fuzzy Systems, 19(3), 527–539. https://doi.org/10.1109/TFUZZ.2011.2116029
   Web of Science ®Google Scholar
• Pelissari, R., Oliveira, M. C., Ben Amor, S., & Abackerli, A. J. (2019). A new FlowSort-based method to deal with information imperfections in sorting decision-making problems. European Journal of Operational Research, 276(1), 235–246. https://doi.org/10.1016/j.ejor.2019.01.006
   Web of Science ®Google Scholar
• Rahmanimanesh, M., Nikabadi, M. S., Pourkarim, F., & Davoodifar, G. (2017). Using fuzzy flowsort inference system to rank the factors leading to failure for ERP projects among Iranian enterprises. Journal of Information Technology Management, 9(4), 787–808. https://doi.org/10.22059/jitm.2017.232070.2019
   Google Scholar
• Ramkumar, M., Schoenherr, T., & Jenamani, M. (2016). Risk assessment of outsourcing e-procurement services: Integrating SWOT analysis with a modified ANP-based fuzzy inference system. Production Planning & Control, 27(14), 1171–1190. https://doi.org/10.1080/09537287.2016.1190877
   Web of Science ®Google Scholar
• Rodriguez, R. M., Martinez, L., & Herrera, F. (2012). Hesitant fuzzy linguistic term sets for decision making. IEEE Transactions on Fuzzy Systems, 20(1), 109–119. https://doi.org/10.1109/TFUZZ.2011.2170076
   Web of Science ®Google Scholar
• Sarwar Sindhu, M., Rashid, T., & Khan, M. (2019). Group decision making based on hesitant fuzzy ranking of hesitant fuzzy preference relations. Journal of Intelligent & Fuzzy Systems, 37(2), 2563–2573. https://doi.org/10.3233/JIFS-182780
   Web of Science ®Google Scholar
• Singh, P. (2021). The role of teachers in motivating students to learn. Technolearn An International Journal of Educational Technology, 11(1), https://doi.org/10.30954/2231-4105.01.2021.6
   Google Scholar
• Takami, M. A., Sheikh, R., & Sana, S. S. (2018). A hesitant fuzzy set theory based approach for project portfolio selection with interactions under uncertainty. Journal of Information Science and Engineering, 34(1), 65–79. https://doi.org/10.6688/JISE.2018.34.1.5
   Web of Science ®Google Scholar
• Tejeda-Lorente, A., Bernabé-Moreno, J., Porcel, C., & Herrera-Viedma, E. (2014). Integrating quality criteria in a fuzzy linguistic recommender system for digital libraries. Procedia Computer Science, 31, 1036–1043. https://doi.org/10.1016/j.procs.2014.05.357
   Google Scholar
• Torra, V. (2010). Hesitant fuzzy sets. International Journal of Intelligent Systems, 25(6), 529–539. https://doi.org/10.1002/int.20418
   Web of Science ®Google Scholar
• Torra, V., & Narukawa, Y. (Aug. 2009). On hesitant fuzzy sets and decision. 2009 IEEE International Conference on Fuzzy Systems, pp. 1378–1382.
   Google Scholar
• Wan, S., Zhong, L., & Dong, J. (2020). A new method for group decision making with hesitant fuzzy preference relations based on multiplicative consistency. IEEE Transactions on Fuzzy Systems, 28(7), 1449–1463. https://doi.org/10.1109/TFUZZ.2019.2914008
   Web of Science ®Google Scholar
• Wan, S. P., Qin, Y. L., & Dong, J. Y. (2017). A hesitant fuzzy mathematical programming method for hybrid multi-criteria group decision making with hesitant fuzzy truth degrees. Knowledge-Based Systems, 138, 232–248. https://doi.org/10.1016/j.knosys.2017.10.002
   Web of Science ®Google Scholar
• Wan, S. P., Zou, W. C., Zhong, L. G., & Dong, J. Y. (2020). Some new information measures for hesitant fuzzy PROMETHEE method and application to green supplier selection. Soft Computing, 24(12), 9179–9203. https://doi.org/10.1007/s00500-019-04446-w
   Web of Science ®Google Scholar
• Wang, C., Li, Q., Zhou, X., & Yang, T. (2014). Hesitant triangular fuzzy information aggregation operators based on bonferroni means and their application to multiple attribute decision making. The Scientific World Journal, 2014, 1–15. https://doi.org/10.1155/2014/648516
   Google Scholar
• Wang, J. Q., Wu, J. T., Wang, J., Zhang, H. Y., & Chen, X. H. (2014). Interval-valued hesitant fuzzy linguistic sets and their applications in multi-criteria decision-making problems. Information Sciences, 288(1), 55–72. https://doi.org/10.1016/j.ins.2014.07.034
   Google Scholar
• Xia, M., & Xu, Z. (2011). Hesitant fuzzy information aggregation in decision making. International Journal of Approximate Reasoning, 52(3), 395–407. https://doi.org/10.1016/j.ijar.2010.09.002
   Web of Science ®Google Scholar
• Xu, G. L., Wan, S. P., & Dong, J. Y. (2016). A hesitant fuzzy programming method for hybrid MADM with incomplete attribute weight information. Informatica, 27(4), 863–892. https://doi.org/10.15388/Informatica.2016.115
   Web of Science ®Google Scholar
• Xu, X., Wang, Y., & Yu, S. (2018). Teaching performance evaluation in smart campus. IEEE Access, 6, 77754–77766. https://doi.org/10.1109/ACCESS.2018.2884022
   Web of Science ®Google Scholar
• Yager, R. R. (1986). On the theory of bags. International Journal of General Systems, 13(1), 23–37. https://doi.org/10.1080/03081078608934952
   Web of Science ®Google Scholar
• Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
   Google Scholar
• Zou, W. C., Wan, S. P., & Chen, S. M. (2022). A fairness-concern-based LINMAP method for heterogeneous multi-criteria group decision making with hesitant fuzzy linguistic truth degrees. Information Sciences, 612, 1206–1225. https://doi.org/10.1016/j.ins.2022.08.111
   Web of Science ®Google Scholar