The Semester Timetabling Problem Based On Satisfaction With Course Selection

Course selection and timetabling are components of educational administration job, playing a quite important role in maintaining the order and the quality of teaching. As one of the most common combinatorial optimization problems, course timetabling is quite a complex job due to its characteristics of large scale and numerous factors. This paper describes a semester course timetabling problem based on students' satisfaction with course selection which embarks from a real-world university course timetabling problem, and the main contributions of the thesis are as follows. Firstly, the characteristics of this timetabling problem are described. A semester timetabling based on course selection is considered and concepts like students' course preferences form and satisfaction with course selection are introduced. Then, the combination of weeks and timeslots can make full use of teaching resources and is more practical. Besides, considering that one professor may teach more than one course can do good to the optimization of resources in a reasonable manner. Secondly, A new model is developed for a semester timetabling problem based on satisfaction of course selection with numerous constraints. The combination of course timetabling with course selection develops the content of research on course timetabling. Finally, in the solution phase, a three phase algorithm is established. first, data like conflict matrix between courses is stored through data preprocessing in the beginning, and then an initial feasible solution is obtained quickly through the constructing method based on course priority, and in the last step, a local search method is carried out to get a “nice” timetable, and computational results showed its effectiveness through the real data compared with the results obtained from the curriculum-based timetabling problem. It also provides a theoretical basis and technical support for university timetabling problem with course selection.