<![CDATA[Scheduling problems in school environments often present significant challenges due to the involvement of numerous variables and constraints, such as teacher availability, classroom allocation, and balanced subject distribution. Manual scheduling tends to be time-consuming and prone to errors, necessitating a more efficient and adaptive solution. This study aims to design and implement an automatic scheduling system using a Genetic Algorithm. This algorithm is chosen for its capability to solve optimization problems with complex solution spaces. The development process involves representing chromosomes as combinations of schedule elements, selecting based on conflict levels, and applying genetic operators such as crossover and mutation to generate optimal solutions. Test results show that the system is capable of producing high-quality schedules with minimal conflicts and efficient computation time. This approach significantly enhances the speed, accuracy, and flexibility of school scheduling systems]]>
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