Design And Implementation Of Graduate Class Scheduling And Paper System Based On Improved Genetic Algorithm

In order to implement the "Opinions on Accelerating the Reform and Development of Graduate Education in the New Era" proposed by the Ministry of Education,many universities have set the goal of improving the disciplinary system and constructing a curriculum system that reflects the characteristics of their respective fields.They have also added a large number of professional courses that reflect the needs of their disciplinary fields.However,due to the continuous increase in the total number of graduate students in recent years,the workload of scheduling classes and organizing exams has increased.Since scheduling classes and organizing exams are important components of graduate teaching management and have a direct impact on the rationality of teaching plans,this article focuses on the problem of scheduling classes and organizing exams for graduate students and uses genetic algorithm as the basic idea to solve the two types of problems.However,genetic algorithms are prone to local optimization and slow convergence during the operation process.Therefore,this article proposes an improved genetic algorithm-based graduate scheduling algorithm and an improved genetic algorithm-based intelligent exam paper organizing algorithm.The specific research contents are as follows:(1)Proposed an improved genetic algorithm-based graduate scheduling algorithm.Based on the mathematical model of graduate scheduling problem,a real number coding scheme and an fitness function for measuring the quality of the class schedule were designed.In terms of genetic operators,the roulette wheel selection method was first used to select individuals in the population,and then a single-point crossover operation and a basic bit operation mutation operation were performed through an adaptive strategy to increase the diversity of the population and improve the optimization ability of the algorithm,while ensuring that the structure of the chromosome was not destroyed.Finally,population individual optimization operation was introduced to determine whether the poorer individuals in the old population would be inherited to the next generation,so as to eliminate local optimization and improve convergence.Through experimental comparative analysis,the algorithm proposed in this article can generate more reasonable class schedules.(2)Proposed an improved genetic algorithm-based intelligent exam paper organizing algorithm.Based on the mathematical model of exam paper organizing problem,a segmented real number coding scheme based on question types and a fitness function for measuring the quality of the exam paper were designed.In terms of genetic operators,the roulette wheel selection method was first used to select individuals in the population,and then designed an adaptive two-point crossover operation based on the same question type and an adaptive segmented variation operation based on the same question type.Finally,population individual optimization operation was introduced.Through experimental comparative analysis,the algorithm proposed in this article can generate higher-quality exam papers.(3)Designed and implemented a graduate scheduling and exam paper organizing system based on improved genetic algorithm.First,the overall framework of the system was analyzed and designed.Then,combining the two algorithms proposed in this article,the graduate scheduling and exam paper organizing system based on improved genetic algorithm was implemented using Java and Vue frameworks.Finally,through testing,the system can run and be used normally,and can effectively complete the work of scheduling classes and organizing exams for graduate students,thereby improving the work efficiency of teaching staff.