An Improved Adaptive Genetic Algorithm and Its Application in Intelligent Course Scheduling System

The application field of modern information technology is expanding, the practical engineering problems are complex and diverse, and the shortcomings of traditional genetic algorithms are gradually emerging. In the course scheduling problem, the NP-hard problem of multi-constraint complex combination optimization is difficult to be solved by traditional genetic algorithm. In this paper, the initial population homogenization, coding design, adaptive crossover mutation operator and conflict detection methods of traditional genetic algorithm are improved,and a new adaptive genetic algorithm is designed. Based on this, a mathematical model of the intelligent course scheduling system is established.The experimental results show that the new adaptive genetic algorithm has greatly improved the convergence speed and the global optimal solution. The efficiency of class scheduling in the course scheduling system is greatly improved, which provides new ideas and methods for the intelligent class scheduling problem.