An Improved Adaptive Genetic Algorithm And Its Application Research In Intelligent Course Arrangement System

Genetic algorithm,as a self-organizing and adaptive artificial intelligence technology for solving problems,provides an effective tool for general combinatorial optimization problems.However,with the continuous expansion of the application field of modern information technology and the complexity and variety of practical engineering problems,the deficiencies of traditional genetic algorithms have gradually emerged.In the intelligent course scheduling problem,the NP-hard problem of multi-constrained complex combination optimization is difficult to solve,which is difficult to solve by using traditional genetic algorithms.At present,smart campuses and one-stop online service halls are widely used in the construction of digital campuses in colleges and universities.With the implementation of the expansion of enrollment policies,tremendous changes have also occurred in the management of college education under various teaching modes and environmental constraints,solving the problem of intelligent curriculum arrangement in colleges and universities very meaningful.In this paper,the initial population,coding design,adaptive crossover and mutation operators and conflict detection methods of traditional genetic algorithms are studied,using the operator with better performance,the crossover rate and the mutation rate are adjusted nonlinearly according to the individual fitness between the average fitness and the maximum fitness.An improved new adaptive genetic operator is constructed.An improved new adaptive genetic algorithm makes the algorithm jump out of the local optimal solution and improves the accuracy.On this basis,the elements and constraints of college curriculum scheduling are analyzed,and the mathematical model of college intelligent curriculum scheduling system is established,and the improved adaptive genetic algorithm is applied to the college intelligent curriculum scheduling system.Through experiments,it is proved that the improved new adaptive genetic algorithm has improved the convergence speed and the global optimal solution.Under the setting of different scheduling rules,the satisfaction rate of students' course selection reaches 98%,and the average rule satisfaction rate reaches 95.8%,it is applied in the intelligent scheduling system and the overall satisfaction rate raised to 98%,providing new ideas and methods for solving intelligent scheduling problems,making the university curriculum management system more intelligent,and improving teaching resources reasonable allocation and completion of education and teaching plans.At present,the intelligent course scheduling system based on this new and improved adaptive genetic algorithm has passed online and offline tests,has been practically applied in a school in Shunde District,Foshan City,Guangdong Province,and has been successfully deployed on the server of the school experiment center computer room.The function of each module is normal and the system is running well.