Application of Genetic Algorithm and Simulated Annealing Algorithm for Course Scheduling Problem

In this paper, we propose a special course scheduling problem with class combination. By dismantling the restrictions of given classes, students with similar foundations are reorganized into new classes. It helps to improve the efficiency of the class and the acceptance of students. However, it is difficult to arrange new classes and time artificially, considering class capacity and the conflict with other courses. And as the number of class increases, the calculation time shows an exponential growth, which is an NP-hard problem. In order to solve this problem, we use genetic algorithm and simulated annealing algorithm to get the optimal solution. Introduction As one of the core contents of teaching management, class scheduling is an important indicator to measure the level of teaching management.[1] The intelligent automatic course arrangement is a NP-hard problem.[2] Nowadays, many universities face the problem of class recombination. That is, due to the different original capabilities of students, it is necessary to reorganize classes just for a certain course, to help the new class become more efficient and more active. In this paper, we use genetic algorithm and simulated annealing algorithm to discuss the course scheduling problem with class recombination, and analyze their results respectively. Our experiments come from real situation in the University of Science and Technology Beijing, taking the subject of English as an example. Problem Description We need to arrange English classes for 120 given classes. There are seven feasible periods, which are Tuesday's 1st, 2nd and 3rd lessons and Wednesday's 1st, 2nd, 3rd and 4th lessons. Before the English class, the Mathematics class time has been arranged, which is available for the 1st, 2nd and 3rd lessons on Monday, Wednesday, and Friday. According to the existing schedule, the time of the English class and the Mathematics class cannot be conflicted, and the course arrangement of the English class also has the following requirements: 1. The students are divided into five levels, each of which accounts for 10%, 10%, 20%, 40%, 20%. So there are five levels in each class. But the proportion of five levels in these classes is different, and it should be ensured that the sum of students of each level is equal to the pre-set proportion. 2. There are seven optional periods. Because the number of students in classes varies, we should pay attention to combine large and small classes, so that the number of new classes in each period is similar. 3. All students are divided into 7 periods. The number of students in each period should be equal to 1/7 of total students. At the same time, the number of students in each period is divided into 2-5 according to English level. and the ratio should be 1:2:4:2. As we can see, this problem belongs to integer programming, the equality of the above requirements can not be fully satisfied, so in the actual solution, we weaken it to the minimum error, that is, the difference between the final results and the above requirements is the smallest. International Conference on Modeling, Analysis, Simulation Technologies and Applications (MASTA 2019) Copyright © 2019, the Authors. Published by Atlantis Press. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/). Advances in Intelligent Systems Research, volume 168