Multi-Criteria Decision Making Model For Hotel Selection Problem Under Complex Dual Hesitant Fuzzy Information

References

• Ali, Z., and T. Mahmood. 2020a. Complex neutrosophic generalised dice similarity measures and their application to decision making. CAAI Transactions on Intelligence Technology 5 (2):78–39. doi:10.1049/trit.2019.0084.
   Google Scholar
• Ali, Z., and T. Mahmood. 2020b. Maclaurin symmetric mean operators and their applications in the environment of complex q-rung orthopair fuzzy sets. Computational and Applied Mathematics 39 (3):1–27. doi:10.1007/s40314-020-01145-3.
   Google Scholar
• Ali, Z., T. Mahmood, K. Ullah, and Q. Khan. 2021. Einstein geometric aggregation operators using a novel complex interval-valued pythagorean fuzzy setting with application in green supplier chain management. Reports in Mechanical Engineering 2 (1):105–134. doi:10.31181/rme2001020105t.
   Google Scholar
• Alkouri, A. M. D. J. S., and A. R. Salleh, 2012. Complex intuitionistic fuzzy sets. In AIP conference proceedings, September, American Institute of Physics, 1482, 464–70. 10.1063/1.4757515.
   Google Scholar
• Atanassov, K. T. 1986. Intuitionistic fuzzy set. Fuzzy Sets and Systems 20 (1):87–96. doi:10.1016/S0165-0114(86)80034-3.
   Web of Science ®Google Scholar
• Beg, I., and T. Rashid. 2014. Multi-criteria trapezoidal valued intuitionistic fuzzy decision making with Choquet integral based TOPSIS. Opsearch 51 (1):98–129. doi:10.1007/s12597-013-0134-5.
   Google Scholar
• Biswas, A., and A. Sarkar. 2018. Development of dual hesitant fuzzy prioritized operators based on Einstein operations with their application to multi-criteria group decision making. Archives of Control Sciences 28 (4):527–49.
   Web of Science ®Google Scholar
• Boran, F. E., S. Genç, M. Kurt, and D. Akay. 2009. A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Systems with Applications 36 (8):11363–11368. doi:10.1016/j.eswa.2009.03.039.
   Web of Science ®Google Scholar
• Das, A. K., and C. Granados. 2022. FP-intuitionistic multi fuzzy N-soft set and its induced FP-Hesitant N soft set in decision-making. Decision making. Decision Making: Applications in Management and Engineering 5 (1):67–89. doi:10.31181/dmame181221045d.
   Google Scholar
• De, S. K., R. Biswas, and A. R. Roy. 2001. An application of intuitionistic fuzzy sets in medical diagnosis. Fuzzy Sets and Systems 117 (2):209–213. doi:10.1016/S0165-0114(98)00235-8.
   Web of Science ®Google Scholar
• Garg, H., T. Mahmood, U. U. Rehman, and Z. Ali. 2021. CHFS: Complex hesitant fuzzy sets-their applications to decision making with different and innovative distance measures. CAAI Transactions on Intelligence Technology 6 (1):93–122. doi:10.1049/cit2.12016.
   Google Scholar
• Garg, H., and D. Rani. 2019. Some generalized complex intuitionistic fuzzy aggregation operators and their application to multicriteria decision-making process. Arabian Journal for Science and Engineering 44 (3):2679–2698. doi:10.1007/s13369-018-3413-x.
   Web of Science ®Google Scholar
• Garg, H., and D. Rani. 2021. New prioritized aggregation operators with priority degrees among priority orders for complex intuitionistic fuzzy information. Journal of Ambient Intelligence and Humanized Computing 14 (3):1373–99. doi:10.1007/s12652-021-03164-2.
   Google Scholar
• Kakati, P., T. Senapati, S. Moslem, and F. Pilla. 2024. Fermatean fuzzy Archimedean Heronian Mean-Based Model for estimating sustainable urban transport solutions. Engineering Applications of Artificial Intelligence 127:107349. doi:10.1016/j.engappai.2023.107349.
   Web of Science ®Google Scholar
• Kefeng, L., and C. Bin, 2017, July. Intuitionistic fuzzy prioritized information aggregation operators based on einstein operations and their applications to MCDM. In 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) (pp. 1479–84). IEEE. doi:10.1109/FSKD.2017.8392983.
   Google Scholar
• Klement, E. P., R. Mesiar, and E. Pap. 2004. Triangular norms. Position paper I: Basic analytical and algebraic properties. Fuzzy Sets and Systems 143 (1):5–26. doi:10.1016/j.fss.2003.06.007.
   Web of Science ®Google Scholar
• Li, D. F. 2005. Multiattribute decision making models and methods using intuitionistic fuzzy sets. Journal of Computer and System Sciences 70 (1):73–85. doi:10.1016/j.jcss.2004.06.002.
   Web of Science ®Google Scholar
• Limboo, B., and P. Dutta. 2022. A q-rung orthopair basic probability assignment and its application in medical diagnosis. Decision Making: Applications in Management and Engineering 5 (1):290–308. doi:10.31181/dmame191221060l.
   Google Scholar
• Liu, P., T. Mahmood, and Z. Ali. 2019. Complex q-rung orthopair fuzzy aggregation operators and their applications in multi-attribute group decision making. Information 11 (1):5. doi:10.3390/info11010005.
   Google Scholar
• Mahmood, T., K. Ullah, Q. Khan, and N. Jan. 2019. An approach toward decision-making and medical diagnosis problems using the concept of spherical fuzzy sets. Neural Computing and Applications 31 (11):7041–7053. doi:10.1007/s00521-018-3521-2.
   Web of Science ®Google Scholar
• Mahmood, T., U. Ur Rehman, Z. Ali, R. Chinram, and C. Zhang. 2020. Jaccard and dice similarity measures based on novel complex dual hesitant fuzzy sets and their applications. Mathematical Problems in Engineering 2020:1–25. doi:10.1155/2020/5920432.
   Web of Science ®Google Scholar
• Moslem, S. 2024. A novel parsimonious spherical fuzzy analytic hierarchy process for sustainable urban transport solutions. Engineering Applications of Artificial Intelligence 128:107447. doi:10.1016/j.engappai.2023.107447.
   Web of Science ®Google Scholar
• Munir, M., H. Kalsoom, K. Ullah, T. Mahmood, and Y. M. Chu. 2020. T-spherical fuzzy Einstein hybrid aggregation operators and their applications in multi-attribute decision making problems. Symmetry 12 (3):365. doi:10.3390/sym12030365.
   Google Scholar
• Ramot, D., R. Milo, M. Friedman, and A. Kandel. 2002. Complex fuzzy sets. IEEE Transactions on Fuzzy Systems 10 (2):171–186. doi:10.1109/91.995119.
   Web of Science ®Google Scholar
• Riaz, M., and H. A. Farid. 2022. Picture fuzzy aggregation approach with application to third-party logistic provider selection process. Reports in Mechanical Engineering 3 (1):318–27. doi:10.31181/rme20023062022r.
   Google Scholar
• Talafha, M., A. U. Alkouri, S. Alqaraleh, H. Zureigat, and A. Aljarrah. 2021. Complex hesitant fuzzy sets and its applications in multiple attributes decision-making problems. Journal of Intelligent & Fuzzy Systems 41 (6):7299–7327. doi:10.3233/JIFS-211156.
   Web of Science ®Google Scholar
• Torra, V. 2010. Hesitant fuzzy sets. International Journal of Intelligent Systems 25 (6):529–539. doi:10.1002/int.20418.
   Web of Science ®Google Scholar
• Torra, V., and Y. Narukawa, 2009. On hesitant fuzzy sets and decision. InThe 18th IEEE International Conference on Fuzzy Systems (pp. 1378–82). Jeju Island, Korea. doi:10.1109/FUZZY.2009.5276884.
   Google Scholar
• Ullah, K., T. Mahmood, and H. Garg. 2020. Evaluation of the performance of search and rescue robots using T-spherical fuzzy Hamacher aggregation operators. International Journal of Fuzzy Systems 22 (2):570–582. doi:10.1007/s40815-020-00803-2.
   Web of Science ®Google Scholar
• Wei, G. 2012. Hesitant fuzzy prioritized operators and their application to multiple attribute decision making. Knowledge-Based Systems 31:176–182. doi:10.1016/j.knosys.2012.03.011.
   Web of Science ®Google Scholar
• Xiao, F., and W. Ding. 2019. Divergence measure of Pythagorean fuzzy sets and its application in medical diagnosis. Applied Soft Computing 79:254–267. doi:10.1016/j.asoc.2019.03.043.
   Web of Science ®Google Scholar
• Xia, M., and Z. Xu. 2011. Hesitant fuzzy information aggregation in decision making. International Journal of Approximate Reasoning 52 (3):395–407. doi:10.1016/j.ijar.2010.09.002.
   Web of Science ®Google Scholar
• Xu, Z. 2007. Intuitionistic fuzzy aggregation operators. IEEE Transactions on Fuzzy Systems 15 (6):1179–1187. doi:10.1109/TFUZZ.2006.890678.
   Web of Science ®Google Scholar
• Yager, R. R. 1977. Multiple objective decision-making using fuzzy sets. International Journal of Man-Machine Studies 9 (4):375–382. doi:10.1016/S0020-7373(77)80008-4.
   Web of Science ®Google Scholar
• Yu, D. 2013. Intuitionistic fuzzy prioritized operators and their application in multi-criteria group decision making. Technological and Economic Development of Economy 19 (1):1–21. doi:10.3846/20294913.2012.762951.
   Web of Science ®Google Scholar
• Yu, D. 2014. Some hesitant fuzzy information aggregation operators based on Einstein operational laws. International Journal of Intelligent Systems 29 (4):320–340. doi:10.1002/int.21636.
   Web of Science ®Google Scholar
• Yu, Q., F. Hou, Y. Zhai, and Y. Du. 2016. Some hesitant fuzzy Einstein aggregation operators and their application to multiple attribute group decision making. International Journal of Intelligent Systems 31 (7):722–746. doi:10.1002/int.21803.
   Web of Science ®Google Scholar
• Zadeh, L. A. 1965. Fuzzy sets. Information & Control 8 (3):338–353. doi:10.1016/S0019-9958(65)90241-X.
   Google Scholar
• Zhao, N., and Z. Xu. 2018. Prioritized dual hesitant fuzzy aggregation operators based on t-norms and t-conorms with their applications in decision making. Informatica 29 (3):581–607. doi:10.15388/Informatica.2018.183.
   Web of Science ®Google Scholar
• Zhao, H., Z. Xu, and S. Liu. 2017. Dual hesitant fuzzy information aggregation with Einstein t-conorm and t-norm. Journal of Systems Science and Systems Engineering 26 (2):240–264. doi:10.1007/s11518-015-5289-6.
   Web of Science ®Google Scholar
• Zhou, X., and Q. Li. 2014. Generalized hesitant fuzzy prioritized Einstein aggregation operators and their application in group decision making. International Journal of Fuzzy Systems 16 (3):303–316.
   Web of Science ®Google Scholar
• Zhu, B., Z. Xu, and M. Xia. 2012. Dual hesitant fuzzy sets. Journal of Applied Mathematics 2012:1–13. Article ID 879629. doi:10.1155/2012/879629.
   Google Scholar