Scheduling is a component of the organization of the educational process. One of the common limitations of scheduling is to minimize the number of "windows" for students. In addition, many Ukrainian universities use a system with a scheduling for even and odd weeks. Therefore, there is a need to automate the scheduling at the university with the specified requirements. Genetic algorithms use the search in several directions in the solution space allowing finding a solution close to optimal in a short time. The accuracy of the solution increases with increasing number of iterations. One of the areas of genetic algorithm application is the scheduling under additional constraints, which lead to a reduction in the range of acceptable solutions and, consequently, reduce the number of scheduling versions in the initial population of the genetic algorithm and scheduling versions obtained by crossing and mutation. This narrows the scope of the stochastic search for a genetic algorithm and can lead to an inefficient solution. To avoid this shortcoming the scheduling is divided into a system of less dimension problems, namely, weekly and odd weekly scheduling, as well as even weekly scheduling. The method has been elaborated, which solves each of the obtained problems by the genetic algorithm. According to the elaborated method, the genetic algorithm is used twice: once to weekly and odd weekly scheduling and the second time to even weekly scheduling. A minimum number of "windows" for students is ensured by the appropriate choice of the fitness function of the genetic algorithm. Automation of scheduling saves a lot of time for employees of the training department. With the use of a genetic algorithm, scheduling versions are obtained, and the employee will have to choose the best one. Scheduling with the elaborated method results in a slightly larger number of "windows" than a manually scheduling. However, manually generating the initial version of the schedule takes much longer than the removal of "windows".