Bipartite graph edge coloring approach to course timetabling

Course timetabling problem is common in schools and higher learning institutions. Courses must be allocated to teachers/lecturers, students, timeslots and venues without violating a set of predefined constraints determined by the respective institution. The problem is complex due to the different requirements set by the institutions and the process of finding a solution can be lengthy and time-consuming. This paper presents our research findings on implementing a bipartite graph edge coloring approach in solving a course timetabling problem. The data set used in this study is gathered from the Department of Information Technology in a Private College. Three data sets (from three different semesters) were tested in our experiment. The results are analyzed by comparing the total penalties of violation on a set of predefined soft constraints between the current timetable (produced manually) and the timetable from our prototype developed. The results from experimental research showed that the bipartite graph edge coloring approach on the course timetabling problem in this case study was able to reduce the penalties, thus producing better quality timetable compared to the manual timetable. In future research, more experiments can be conducted using the bipartite graph edge coloring approach with larger scope of data sets.