Metaheuristic Approaches for Solving University Timetabling Problems: A Review and Case Studies from Middle Eastern Universities
University timetabling problems are concerned with the assignment of events and tasks that occur frequently in universities, like exams, courses, projects, and faculty load. These problems are difficult and consume a lot of time and effort if done manually. Automating such tasks will save time and cost, and increase the satisfaction of the stakeholders. Since university timetabling problems are mostly NP-hard, heuristics and metaheuristics are often used for solving them. In this survey, we review different university timetabling problems, such as: Examination Timetabling, Course Timetabling, and Staff Timetabling. We also propose a new problem, which is Project Timetabling. In addition, we discuss some case studies that successfully tackled these problems using metaheuristic algorithms. However, due to the huge number of papers published worldwide in this research area, we focus in this survey on papers published in the Middle Eastern region. The findings of this survey indicate that there are many challenges that are still open for further investigation. Focusing on the convenience of the stakeholders and adopting hybrid search methods are among the promising research directions in this field. Project timetabling which has been introduced in this survey is also another promising area that is open for further investigation by the interested researchers.
KeywordsScheduling Heuristics Metaheuristics University timetabling problems
The author would like to extend thanks to Mrs. Shameem Fatima for her great efforts in collecting and categorizing the references presented in this survey.
- 2.Hosny, M., Fatima, S.: A survey of genetic algorithms for the university timetabling problem. In: International Proceedings of Computer Science and Information Technology, pp. 34–39 (2011)Google Scholar
- 4.Hosny, M., Al-Olayan, M.: A mutation-based genetic algorithm for room and proctor assignment in examination scheduling. In: Proceedings of 2014 Science and Information Conference, SAI 2014 (2014)Google Scholar
- 6.Hosny, M.I.: A heuristic algorithm for solving the faculty assignment problem. J. Commun. Comput. 10, 287–294 (2013)Google Scholar
- 7.Al-negheimish, S., Alnuhait, F., Albrahim, H., Al-mogherah, S., Alrajhi, M., Hosny, M.: An intelligent bio-inspired algorithm for the faculty scheduling problem. Int. J. Adv. Comput. Sci. Appl. 9, 151–159 (2018)Google Scholar
- 10.Marie-Sainte, S.L.: A new hybrid particle swarm optimization algorithm for real-world university examination timetabling problem. In: 2017 Computing Conference, pp. 157–163 (2017)Google Scholar
- 11.Chmait, N., Challita, K.: Using simulated annealing and ant-colony optimization algorithms to solve the scheduling problem. Comput. Sci. Inf. Technol. 1, 208–224 (2013)Google Scholar
- 12.Alhuwaishel, N., Hosny, M.: A Hybrid Bees/Demon Optimization Algorithm for Solving the University Course Timetabling Problem, pp. 371–378 (2015)Google Scholar
- 14.Al-qubati, W., Zahary, A., Al-hegami, A.: Using nested tables and mutation in genetic algorithms (NTMGA) to solve timetabling problem in object- relational model, pp. 215–221 (2012)Google Scholar
- 15.Alsmadi, O.M.K., Abo-Hammour, Z.S., Abu-Al-Nadi, D.I., Algsoon, A.: A novel genetic algorithm technique for solving university course timetabling problems. In: IEEE International Workshop on Systems, Signal Processing and their Applications, WOSSPA, pp. 195–198 (2011)Google Scholar
- 16.Bolaji, A.L., Khader, A.T., Al-betar, M.A., Awadallah, M.A.: An improved artificial bee colony for course timetabling. In: 2011 Sixth International Conference on Bio-Inspired Computing Theories and Applications, pp. 9–14 (2011)Google Scholar