In the administrative management of colleges and universities, the scheduling is a complex and critical task. The number of subjects and the limited teaching resources all restrict the complexity and results of class scheduling. The essence of class scheduling is to arrange the course and class to the appropriate teaching location at the appropriate time. It is a solution to the NP problem. As the scale continues expanding, the difficulty of solving problems increases exponentially. When the scale reaches a certain level, it is difficult to find the optimal solution in a short time. In view of this, this study proposes a genetic-ant colony hybrid algorithm, which uses a mixture of two algorithms, relies on genetic algorithm to generate pheromone distribution, and uses ant colony algorithm to find the optimal solution. The experimental results show that the hybrid algorithm improves the efficiency of class scheduling and the rationality of the class schedule.