Optimizing Subject Planning in University Curriculum via the Genetic Algorithm: An Evaluation Study

This paper presents a comprehensive evaluation of a Genetic Algorithm (GA) framework designed to optimize subject planning in university curricula, with a specific focus on Sunway University’s academic environment. Academic planning, often constrained by prerequisites, credit hour limits, and semester-specific course offerings, poses significant challenges in ensuring timely graduation and resource efficiency. The proposed GA framework integrates institution-specific constraints into a customized fitness function, enabling the generation of optimized and practical subject plans. Through rigorous evaluation, the system achieved subject plan generation in under two seconds while ensuring complete adherence to all academic constraints. The results highlight the adaptability and scalability of GAs in solving complex academic scheduling problems, offering a robust and efficient approach to curriculum optimization in higher education institutions.