Optimizing Lecture Scheduling Using Genetic Algorithm: A Case Study at Universitas Riau
Lecture scheduling is a complex and essential task in academic settings, particularly for optimizing the use of resources such as classrooms, time slots, and teaching staff. This study developed a web-based lecture scheduling application using a genetic algorithm for the Faculty of Engineering, Univ...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Universitas Riau
2025-06-01
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| Series: | International Journal of Electrical, Energy and Power System Engineering |
| Subjects: | |
| Online Access: | https://ijeepse.id/journal/index.php/ijeepse/article/view/202 |
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| Summary: | Lecture scheduling is a complex and essential task in academic settings, particularly for optimizing the use of resources such as classrooms, time slots, and teaching staff. This study developed a web-based lecture scheduling application using a genetic algorithm for the Faculty of Engineering, University of Riau. Genetic algorithms were selected due to their effectiveness in solving complex optimization problems and producing efficient solutions in a relatively short time. The application successfully generated conflict-free schedules that met the faculty’s requirements, encompassing 634 courses, 345 lecturers, 38 classrooms, and 12 study programs. The best outcome was achieved in test 7, with a population size of 40, 100 generations, 75% crossover probability, 10% mutation probability, a fitness value of 1, and a generation time of approximately 5 hours and 8 minutes. These results demonstrate the potential of genetic algorithms to streamline the scheduling process, reduce administrative workload, and enhance operational efficiency. This research offers a practical tool for academic institutions and highlights the real-world applicability of advanced computational methods in education management. |
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| ISSN: | 2654-4644 |