<![CDATA[A perfect solution to the challenging issue of course scheduling is needed to prevent scheduling conflicts and guarantee a fair allocation of courses. The effectiveness of genetic algorithms (GA) and genetic algorithms combined with bee algorithms (GA+BA) for automatic course scheduling is compared in this study. this research also investigates the enhancement of performance by the use of the Bee Algorithm, a recognized expert in exploration and exploitation techniques. According to experimental data, when compared to GA alone, GA+BA consistently yields greater fitness values but the computation time increases. The results show that GA only achieves an average fitness value of 0.86, while GA+BA achieves an average fitness value of 0.98. However, GA+BA calculates an average computing time of 14.41 seconds slower, than GA which takes 8.59 seconds. These findings show that combining BA into the GA framework is able to optimally improve the solution to the problem of scheduling practicum courses. This study shows that GA+BA is a successful method in terms of automatic course scheduling, which provides a solution for use in actual.]]>
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