An Enhanced Course Scheduling System Using the Genetic Algorithm with Matrix-Based Representation Genes

Scheduling is a classical problem that involves assigning events to specific times, such as in the transportation, hospitality, and education sectors. In higher education, organizing courses can be particularly challenging due to constraints like the maximum number of classes a teacher can handle daily, avoiding overlapping courses for the same teacher, and ensuring a room is used for only one course at a time. These complex constraints require significant resources and time to construct an optimized schedule. We develop a Genetic Algorithm (GA)-based course scheduling method using a Genetic Algorithm on a web-based application to handle multiple constraints. Our experiments demonstrated that our proposed algorithm provides optimized solutions with minimized constraint violations. The number of constraint violations remained relatively stable regardless of changes in the number of courses, rooms, and sessions, which indicate consistent performances across different scenarios.