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Optimization Techniques in University Timetabling Problem: Constraints, Methodologies, Benchmarks, and Open Issues

Abeer Bashab1, Ashraf Osman Ibrahim2,*, Ibrahim Abakar Tarigo Hashem3, Karan Aggarwal4, Fadhil Mukhlif5, Fuad A. Ghaleb5, Abdelzahir Abdelmaboud6

1 Faculty of Computer Science & Information Technology, Alzaiem Alazhari University, 13311, Khartoum, Sudan
2 Faculty Computing and Informatics, Universiti Malaysia Sabah, Kota Kinabalu, 88400, Sabah, Malaysia
3 Department of Computer Science, University of Sharjah, Sharjah, 27272, United Arab Emirates
4 Electronic and Communication Engineering Department, Maharishi Markandeshwar Deemed to be University, Mullana, Ambala, 133207, Haryana, India
5 Information Assurance and Security Research Group (IASRG), School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, 81310, Johor, Malaysia
6 Department of Information Systems, King Khaled University, Muhayel, 61913, Aseer, Saudi Arabia

* Corresponding Author: Ashraf Osman Ibrahim. Email: email

Computers, Materials & Continua 2023, 74(3), 6461-6484. https://doi.org/10.32604/cmc.2023.034051

Abstract

University timetabling problems are a yearly challenging task and are faced repeatedly each semester. The problems are considered non-polynomial time (NP) and combinatorial optimization problems (COP), which means that they can be solved through optimization algorithms to produce the aspired optimal timetable. Several techniques have been used to solve university timetabling problems, and most of them use optimization techniques. This paper provides a comprehensive review of the most recent studies dealing with concepts, methodologies, optimization, benchmarks, and open issues of university timetabling problems. The comprehensive review starts by presenting the essence of university timetabling as NP-COP, defining and clarifying the two formed classes of university timetabling: University Course Timetabling and University Examination Timetabling, illustrating the adopted algorithms for solving such a problem, elaborating the university timetabling constraints to be considered achieving the optimal timetable, and explaining how to analyze and measure the performance of the optimization algorithms by demonstrating the commonly used benchmark datasets for the evaluation. It is noted that meta-heuristic methodologies are widely used in the literature. Additionally, recently, multi-objective optimization has been increasingly used in solving such a problem that can identify robust university timetabling solutions. Finally, trends and future directions in university timetabling problems are provided. This paper provides good information for students, researchers, and specialists interested in this area of research. The challenges and possibilities for future research prospects are also explored.

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APA Style
Bashab, A., Ibrahim, A.O., Hashem, I.A.T., Aggarwal, K., Mukhlif, F. et al. (2023). Optimization techniques in university timetabling problem: constraints, methodologies, benchmarks, and open issues. Computers, Materials & Continua, 74(3), 6461-6484. https://doi.org/10.32604/cmc.2023.034051
Vancouver Style
Bashab A, Ibrahim AO, Hashem IAT, Aggarwal K, Mukhlif F, Ghaleb FA, et al. Optimization techniques in university timetabling problem: constraints, methodologies, benchmarks, and open issues. Comput Mater Contin. 2023;74(3):6461-6484 https://doi.org/10.32604/cmc.2023.034051
IEEE Style
A. Bashab et al., "Optimization Techniques in University Timetabling Problem: Constraints, Methodologies, Benchmarks, and Open Issues," Comput. Mater. Contin., vol. 74, no. 3, pp. 6461-6484. 2023. https://doi.org/10.32604/cmc.2023.034051



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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