For every school in USM, at the start of the semester, a list of courses offered will be listed with assigned lecturers. At the same time, each school will have a dedicated series of class venues. The timetable scheduler team is responsible to construct a feasible schedule for all courses so there is no redundant venue usage, lecturers' time, students' time, and the timetable must comply with the required hours rules for all courses. Not only that, all students are required to take a few courses outside of their school as a university requirement, either as minor courses, university courses, or language courses. There is also a dedicated slot for co-curricular and clubs activities. All these school and university requirements create a very complex computation in order to build a complete and feasible timetable for every student in each individual school.

Thus, this project goal is to come out with the most optimal solution for each program in every school. Since the complex computation also required a very sophisticated process, the Genetic Algorithm (GA) is implemented inside the Automatic Timetable Generator. Imitating the chromosome behaviour with biological operations such as mutation, crossover and selection. GA opens the possibilities of automatically generating timetable that can try its best not to violate the constraints set by the university and the school's requirements.

This project is implemented with the School of Computer Sciences in mind but has also been tested using two other schools' data: the School of Industrial Technology and the School of Biological Sciences, USM to test the limit of the system capabilities. This project is expected to increase the efficiency and the effectiveness of the respective school scheduler team in designing the timetable, with the advantage of the system’s ability to automatically generate timetables based on individual lecturers, individual venues, and respective students based on batches.