A Review of Optimization Algorithms for University Timetable Scheduling

Authors

  • H. Alghamdi College of Computer and Information Systems, Umm Al Qura University, Saudi Arabia
  • T. Alsubait College of Computer and Information Systems, Umm Al Qura University, Saudi Arabia
  • H. Alhakami College of Computer and Information Systems, Umm Al Qura University, Saudi Arabia
  • A. Baz College of Computer and Information Systems, Umm Al Qura University, Saudi Arabia
Volume: 10 | Issue: 6 | Pages: 6410-6417 | December 2020 | https://doi.org/10.48084/etasr.3832

Abstract

The university course timetabling problem looks for the best schedule, to satisfy given criteria as a set of given resources, which may contain lecturers, groups of students, classrooms, or laboratories. Developing a timetable is a fundamental requirement for the healthy functioning of all educational and administrative parts of an academic institution. However, factors such as the availability of hours, the number of subjects, and the allocation of teachers make the timetable problem very complex. This study intends to review several optimization algorithms that could be applied as possible solutions for the university student course timetable problem. The reviewed algorithms take into account the demands of institutional constraints for course timetable management.

Keywords:

timetabling, genetic algorithms, Particle Swarm Optimization (PSO)

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References

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H. Alghamdi, T. Alsubait, H. Alhakami, and A. Baz, “A Review of Optimization Algorithms for University Timetable Scheduling”, Eng. Technol. Appl. Sci. Res., vol. 10, no. 6, pp. 6410–6417, Dec. 2020.

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