A Study on Optimizing Physical Education Curriculum Scheduling Using Data Flow Analysis Algorithm

Abstract

In order to improve the speed and accuracy of large and complex information processing, the use of data flow analysis technology and to replace the traditional manual scheduling is an inevitable requirement for the quality improvement of higher education. Based on the basic concept of data flow analysis, this paper proposes the use of data flow analysis in different situations. Considering the actual demand of constraints, the scheduling problem is divided into hard and soft constraints, and a multi-objective optimization constraints mathematical model is constructed for physical education course scheduling. Using genetic algorithm, the sports course scheduling problem is optimized and solved. Test the performance of the algorithm in the actual operation and the use of the effect, the model in the completion of the iteration score of 97.058, the whole process takes no more than 2.5 s. Before and after the optimization of scheduling program students change classroom per capita time consumption of 10.04 min and 6.93 min, respectively, the passage of the time consumption reduced by 30.98%, the algorithm used in this paper effectively reduces the passage of time, the physical education course schedule The algorithm used in this paper effectively reduces the passage time and plays an optimizing role in the schedule of physical education courses.