An optimized solution to the course scheduling problem in universities under an improved genetic algorithm

Abstract The increase in the size of universities has greatly increased number teachers, students, and courses also difficulty scheduling courses. This study used coevolution to improve genetic algorithm applied it solve course problem universities. Finally, simulation experiments were conducted on traditional improved algorithms MATLAB software. results showed that converged faster produced better solutions than under same crossover mutation probability. As probability increased, fitness values both gradually decreased, computation time increased. With algorithm, value two first then computational decreased