References
- Augeri, M. G., Cozzo, P., Greco, S. (2015) Dominance based rough set approach: An application case study for setting speed limits for vehicles in speed controlled zones. Knowledge Based Systems, 89, 288–300. DOI: 10.1007/11681960_3.
- Chakhar, S., Ishizaka, A., Labib, A., Saad, I. (2016) Dominance-based rough set approach for group decisions. European Journal of Operational Research, 251, 206–224. DOI:10.1016/j.ejor.2015.10.060.
- Chakhar, S., Saad, I. (2012) Dominance based rough set approach for groups in multicriteria classification problem. Decision Support Systems, 54, 372–380. DOI:10.1016/j.ejor.2015.10.060.
- Chang, Y., Zhu, X., Yan, B., Wang, L. (2017) Integrated scheduling of handling operations in railway container terminals. Transportation Letters, 11(4), 402–412.
- Chen, D., Ni, S., Xu, C., Jiang, X. (2019) Optimizing the draft passenger train timetable based on node importance in a railway network. Transportation Letters, 11(1), 20–32. DOI:10.1080/19427867.2016.1271523.
- Chen, J., Zhu, P. (2024) Feature selection of dominance-based neighborhood rough set approach for processing hybrid ordered data. International Journal of Approximate Reasoning, 167, 109134. DOI:10.1016/j.ijar.2024.109134.
- Chen, T., Guestrin, C. (2016) XGBoost: A scalable tree boosting system. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, August 2016. New York: Association for Computing Machinery, pp. 785–794.
- Cortes, C., Vapnik, V. (1995) Support-vector networks. Machine Learning, 20(3), 273–297. DOI:10.1007/BF00994018.
- Du, W. S., Hu, B. Q. (2016) Dominance-based rough set approach to incomplete ordered information systems. Information Sciences, 346–347, 106–129. DOI:10.1016/j.ins.2016.01.098.
- Givoni, M., Chen, X. (2017) Airline and railway disintegration in China: The case of Shanghai Hongqiao Integrated Transport Hub. Transportation Letters, 9(4), 202–214. DOI:10.1080/19427867.2016.1252877.
- Greco, S., Matarazzo, B., Slowinski, R. (1998) A new rough set approach to multicriteria and multiattribute classification. In: Proceedings of Rough Sets and Current Trends in Computing Conference RSCTC, Warsaw, June 1998. Berlin Heidelberg: Springer-Verlag, pp. 60–67.
- Greco, S., Matarazzo, B., Slowinski, R. (1999) The use of rough sets and fuzzy sets in MCDM. International Series in Operations Research & Management Science, 21. DOI:10.1007/978-1-4615-5025-9_14.
- Greco, S., Matarazzo, B., Slowinski, R. (2001) Rough sets theory for multicriteria decision analysis. European Journal of Operational Research, 129, 1–47. DOI:10.1016/S0377-2217(00)00167-3.
- Greco, S., Matarazzo, B., Slowinski, R., Stefanowski, J. (2001) An algorithm for induction of decision rules consistent with dominance principle. In: Proceedings of Rough Sets and Current Trends in Computing Conference RSCTC, Baniff, October 2000. Berlin Heidelberg: Springer, pp. 304-313.
- Indian Railways. (2025) Indian Railways Information System (IRIS). Available at: https://indiarailinfo.com/train.
- Jiten, S., Gaurang, J., Purnima, P., Shriniwas, A. (2017) Effect of directional distribution on stairway capacity at a suburban railway station. Transportation Letters, 9(2), 70–80.
- Li, S., Li, T., Zhang, Z., Chen, H., Zhan, J. (2015) Parallel computing of approximations in dominance-based rough set approach. Knowledge Based Systems, 87, 102–111.
- Liou, J. H., Tzeng, G. H. (2010) A dominance-based rough set approach to customer behaviour in the airline market. Information Sciences, 180, 2230–2238. DOI:10.1016/j.ins.2010.01.025.
- Majumder, S., Singh, A., Singh, A., Karpenko, M., Sharma, H. K., Mukhopadhyay, S. (2024) On the analytical study of the service quality of Indian Railways under soft-computing paradigm. Transport, 39(1), 54-63. DOI:10.3846/transport.2024.21385.
- Nawaz, U., Saeed, Z., Atif, K. (2025) A novel framework for efficient dominance-based rough set approximations using K-dimensional (KD) tree partitioning and adaptive recalculations techniques. Engineering Applications of Artificial Intelligence, 154, 110993. DOI:10.1016/j.engappai.2025.110993
- Nosheen, F., Qamar, U., Raza, M. S. (2022) A parallel rule-based approach to compute rough approximations of dominance based rough set theory. Engineering Applications of Artificial Intelligence, 115, 105285. DOI:10.1016/j.engappai.2022.105285.
- Pawlak, Z. (1982) Rough sets. International Journal of Computer and Information Science, 11, 341–356.
- Poznan University of Technology. (2006a) 4eMka2 software. Available at: https://fcds.cs.put.poznan.pl/IDSS/software/4emka2.htm.
- Poznan University of Technology. (2006b) ROSE2 software. Available at: https://fcds.cs.put.poznan.pl/IDSS/software/rose.htm.
- Sawicki, P., Zak, J. (2014) The application of dominance based rough set theory to evaluation of transportation systems. Procedia – Social and Behavioral Sciences, 111, 1238-1248.
- Sharma, H. K., Kar, S. (2018). Decision making for hotel selection using rough set theory: A case study of Indian hotels. International Journal of Applied Engineering Research, 13(6), 3988-3998.