A Review of Optimization Algorithms for University Timetable Scheduling

H Alghamdi,T Alsubait,A Baz,H Alhakami

doi:10.48084/etasr.3832

H Alghamdi, T Alsubait + Show 2 more

Open Access

https://doi.org/10.48084/etasr.3832

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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.

Highlights

A Review of Optimization Algorithms for University Timetable SchedulingAbstract—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
Many higher education institutions have teaching staff from various fields, who work together to meet the educational goals set
The university timetabling problem is an example of a Non-Polynomial (NP)-hard problem [4]

Summary

A Review of Optimization Algorithms for University Timetable Scheduling

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. 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

INTRODUCTION

RELATED WORDK

Particle Swarm Optimization

DISCUSSION

CONCLUSION