Research On Course Scheduling System In Open Education Based On Genetic Algorithm

The course scheduling problem has been proved to be a NP complete problem,which has the multi-objective optimization characteristics.It is one of the most widely used methods to solve the course scheduling problem by artificial intelligence.With the gradual expansion scale of colleges and universities and the deepening of the teaching management information reform,the rational allocation of teaching resources has become the key to the course arrangement in colleges and universities.The operation management of open education is different from the traditional higher education,which has many characteristics such as more professional setting and quick update,large number of courses,different teaching hours,and the prominent contradiction between the object of study and work.Based on the study of the relevant literature and basic theory of course scheduling deeply,this paper compares the characteristics of various optimization algorithms and discusses the application fields of solving problems,then genetic algorithm is used to solve the problem of open education.Firstly,this paper gives a solution to the open education course scheduling system based on RUP system development model.The UML modeling technology is used to model the system requirements,structure modeling and database modeling,and the main function structure and requirements of the course scheduling system are described in detail.According to the characteristics and special requirements of open education course scheduling problem,analyzing the relationship of teachers,students,couses,classroom and teaching time,the corresponding models has established using mathematical set and further to build the mathematical modeling for hard constraints and soft constraint conditions.Chromosome coding design and construction of objective function are two key steps to solve the course scheduling problem by genetic algorithm.In this paper,a kind of chromosome design scheme based on three-dimensional spatial coding structure is proposed.Combined with the feasible solution space grid method,the optimal individual replacement strategy,adaptive crossover and mutation probability,the best individual is reserved and the better ability of searching the global optimal solution is obtained.Finally,the experimental comparison results shows that the improvement strategy is effective for solving the open education course scheduling problem,between the improved genetic algorithm and others.And it can be applied to the development of open education course scheduling system.