APPLICATIONS OF OPERATIONS RESEARCH IN REAL-LIFE SCENARIOS: A LITERATURE-BASED STUDY OF CLASSROOM SCHEDULING OPTIMIZATION
AUTHORS:
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Prof. Tejaswini Angre Dwivedi
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BSc. Finance Student, SVKM’s NMIMS ASM School of Commerce, Mumbai, India
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Abstract
Every school and university has to decide which class meets in which room, and when. With a handful of courses this can be worked out on paper, but once there are dozens of courses, lecturers, student groups and shared rooms, manual timetabling becomes slow and clashes slip through. Operations Research (OR) approaches the problem differently: the timetable is written as a mathematical model and handed to a solver. In this study we review twelve published papers that apply OR to classroom, course, examination and school timetabling. Three of them are examined in depth, covering their decision variables, objective functions, constraints, assumptions and solution methods, while the other nine are summarised and compared. We also work through a small example with three classes and three rooms to show how such a model is put together. Integer programming turns out to be the most widely used method, and the largest problems can only be solved in reasonable time with the help of decomposition or heuristics.
Keywords
operations research classroom scheduling timetabling linear programming integer programming assignment problem room utilisation CPLEX Gurobi PuLP tabu search literature review.
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Double-Blind Peer Review
License:
CC BY-NC 4.0
Volume/Issue:
Volume 02, Issue 10
Review Rounds:
2
Article Type:
Research Article
Publication Date:
Oct 08 2026
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Agarwal, K., Mishra, K., Telkar, K., Jhawar, K. & Banka, K. (2026). Applications of Operations Research in Real-Life Scenarios: A Literature-Based Study of Classroom Scheduling Optimization. International Journal of Science, Strategic Management and Technology, 02(10), 1-9. https://doi.org/10.55041/ijsmt.v2i10.020
Agarwal, Keshav, et al.. "Applications of Operations Research in Real-Life Scenarios: A Literature-Based Study of Classroom Scheduling Optimization." International Journal of Science, Strategic Management and Technology, vol. 02, no. 10, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijsmt.v2i10.020.
Agarwal, Keshav,Kaveesh Mishra,Kavin Telkar,Kashvi Jhawar, and Khushal Banka. "Applications of Operations Research in Real-Life Scenarios: A Literature-Based Study of Classroom Scheduling Optimization." International Journal of Science, Strategic Management and Technology 02, no. 10 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijsmt.v2i10.020.
References
[1] Daskalaki, S., Birbas, T., & Housos, E. (2004). An integer programming formulation for a case study in university timetabling. European Journal of Operational Research, 153(1), 117–135. https://doi.org/10.1016/S0377-2217(03)00103-6
[2] Keskin, M. E., Döyen, A., Akyer, H., & Güler, M. G. (2018). Examination timetabling problem with scarce resources: A case study. European Journal of Industrial Engineering, 12(6), 855–874.
[3] Kristiansen, S., Sørensen, M., & Stidsen, T. R. (2015). Integer programming for the generalized high school timetabling problem. Journal of Scheduling, 18, 377–392.
[4] Laisupannawong, T., Sumetthapiwat, S., & Skouri, K. (2024). An integer linear programming model for the examination timetabling problem: A case study of a university in Thailand. Advances in Operations Research, 2024, 1–17. https://doi.org/10.1155/2024/6636563
[5] Lü, Z., & Hao, J.-K. (2010). Adaptive tabu search for course timetabling. European Journal of Operational Research, 200(1), 235–244. https://doi.org/10.1016/j.ejor.2008.12.007
[6] Phillips, A. E., Walker, C. G., Ehrgott, M., & Ryan, D. M. (2017). Integer programming for minimal perturbation problems in university course timetabling. Annals of Operations Research, 252(2), 283–304. https://doi.org/10.1007/s10479-015-2094-z
[7] Phillips, A. E., Waterer, H., Ehrgott, M., & Ryan, D. M. (2015). Integer programming methods for large-scale practical classroom assignment problems. Computers & Operations Research, 53, 42–53. https://doi.org/10.1016/j.cor.2014.07.012
[8] Rappos, E., Thiémard, E., Robert, S., & Hêche, J.-F. (2022). A mixed-integer programming approach for solving university course timetabling problems. Journal of Scheduling, 25, 391–404. https://doi.org/10.1007/s10951-021-00715-5
[9] Rudová, H., Müller, T., & Murray, K. (2011). Complex university course timetabling. Journal of Scheduling, 14(2), 187–207. https://doi.org/10.1007/s10951-010-0171-3
[10] Simarmata, G., Saragih, R., & Syofra, A. H. (2026). University scheduling optimization using integer programming: A case study. CAUCHY: Jurnal Matematika Murni dan Aplikasi, 11(1), 61–74. https://doi.org/10.18860/cauchy.v11i1.37815
[2] Keskin, M. E., Döyen, A., Akyer, H., & Güler, M. G. (2018). Examination timetabling problem with scarce resources: A case study. European Journal of Industrial Engineering, 12(6), 855–874.
[3] Kristiansen, S., Sørensen, M., & Stidsen, T. R. (2015). Integer programming for the generalized high school timetabling problem. Journal of Scheduling, 18, 377–392.
[4] Laisupannawong, T., Sumetthapiwat, S., & Skouri, K. (2024). An integer linear programming model for the examination timetabling problem: A case study of a university in Thailand. Advances in Operations Research, 2024, 1–17. https://doi.org/10.1155/2024/6636563
[5] Lü, Z., & Hao, J.-K. (2010). Adaptive tabu search for course timetabling. European Journal of Operational Research, 200(1), 235–244. https://doi.org/10.1016/j.ejor.2008.12.007
[6] Phillips, A. E., Walker, C. G., Ehrgott, M., & Ryan, D. M. (2017). Integer programming for minimal perturbation problems in university course timetabling. Annals of Operations Research, 252(2), 283–304. https://doi.org/10.1007/s10479-015-2094-z
[7] Phillips, A. E., Waterer, H., Ehrgott, M., & Ryan, D. M. (2015). Integer programming methods for large-scale practical classroom assignment problems. Computers & Operations Research, 53, 42–53. https://doi.org/10.1016/j.cor.2014.07.012
[8] Rappos, E., Thiémard, E., Robert, S., & Hêche, J.-F. (2022). A mixed-integer programming approach for solving university course timetabling problems. Journal of Scheduling, 25, 391–404. https://doi.org/10.1007/s10951-021-00715-5
[9] Rudová, H., Müller, T., & Murray, K. (2011). Complex university course timetabling. Journal of Scheduling, 14(2), 187–207. https://doi.org/10.1007/s10951-010-0171-3
[10] Simarmata, G., Saragih, R., & Syofra, A. H. (2026). University scheduling optimization using integer programming: A case study. CAUCHY: Jurnal Matematika Murni dan Aplikasi, 11(1), 61–74. https://doi.org/10.18860/cauchy.v11i1.37815
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