A MULTI-OBJECTIVE DECISION MAKING MODEL FOR CLASS SELECTION PROBLEM: A CASE STUDY

Abstract

Educational institutions generally present a timetable to students in which the scheduling of courses and classes have been arranged before. Generating an appropriate timetable in which all classes do not conflict each other is quite difficult. Students use this timetable to choose the courses and classes according to their requirements. A selected course class may be conflict with another selected one in timetable. Therefore, students are generally forced in selecting the classes without course conflict or minimum and acceptable course conflict. In this study a computer aided system for engineering students of Industrial Engineering Department at Gazi University is proposed to define the classes for selected courses. The system takes the courses from users and presents them appropriate classes by using a mathematical model in background. The aims of the mathematical model are minimizing the course conflict, assigning student to classes desired by department and minimizing total days in which the student takes courses. Consequently, an easy way is proposed to students in selecting course classes by improving a multi-objective decision making model and a case study is applied. 

 

Keywords

• Student sectioning problem,decision making model,individual student schedule

References

1. Amintoosi, M., & Haddadnia, J. (2004, August). Feature selection in a fuzzy student sectioning algorithm. In PATAT (pp. 147-160). Babaei, H., Karimpour, J., & Hadidi, A. (2015). A survey of approaches for university course timetabling problem. Computers & Industrial Engineering, 86, 43-59. Carter, M. W. (2000). A comprehensive course timetabling and student scheduling system at the University of Waterloo. In Practice and theory of automated timetabling III (pp. 64-82). Springer Berlin Heidelberg. Dostert, M., Politz, A., & Schmitz, H. (2015). A complexity analysis and an algorithmic approach to student sectioning in existing timetables. Journal of Scheduling, 1-9. Kristiansen, S., & Stidsen, T. R. (2012). Adaptive large neighborhood search for student sectioning at Danish high schools. In Proceedings of the Ninth International Conference on the Practice and Theory of Automated Timetabling (PATAT 2012). Kristiansen, S., & Stidsen, T. R. (2014). Elective course student sectioning at Danish high schools. Annals of Operations Research, 1-19. Müller, T., & Murray, K. (2010). Comprehensive approach to student sectioning. Annals of Operations Research, 181(1), 249-269. Müller, T., Murray, K., & Schluttenhofer, S. (2007). University course timetabling & student sectioning system. Space Management and Academic Scheduling, Purdue University.