With an increase in the number of students and the number of courses offered by universities, examination scheduling based on the available facilities becomes much more complicated. At present, examinations must be appropriately scheduled not only based on the offered courses, but also with respect to the rooms’ capacities, available time-slots, days-off rules and other soft and hard constraints. From the Mathematical Programming point of view, timetabling and scheduling problems are somewhat related to Assignment problems, but have additional constraints that make them computationally challenging. Timetabling problems are NP-hard problems for which there is unlikely to be an economically viable method for finding the optimal solution. In our studies, we use Python interfaced with CPLEX as optimization software to find approximately optimal results for large problems in reasonable time.

With an increase in the number of students and the number of courses offered by universities, examination scheduling based on the available facilities becomes much more complicated. At present, examinations must be appropriately scheduled not only based on the offered courses, but also with respect to the rooms capacities, available time-slots, days-off rules and other soft and hard constraints. From the Mathematical Programming point of view, timetabling and scheduling problems are somewhat related to Assignment problems, but have additional constraints that make them computationally challenging. Timetabling problems are NP-hard problems for which there is unlikely to be an economically viable method for finding the optimal solution. In our studies, we use Python interfaced with CPLEX as optimization software to find approximately optimal results for large problems in reasonable time.

This paper describes automated examination scheduling for the Faculty of Information Technology of Brno University of Technology. It specifies a list of restrictions that must by satisfied. Furthermore, this limitations are classified due to their influence on a quality of the final version of the examination schedule. There are two types of restrictions; soft and hard. The task is to find such a solution that satisfies all hard constraints and breaks the minimum of soft constraints using techniques described in this paper.