Customer Story

Efficient exam scheduling thanks to artificial intelligence

For the University of Fribourg, Trivadis implemented a planning tool that makes it easier for the five faculties to coordinate the exams of 10,000 students and 200 professors.

In Short


Outdated stand-alone solution for exam scheduling without integration into the new campus management.


Customised open source solution (CPSolver) with operations research artificial intelligence.


Exam scheduling is more efficient and open to all faculties.

Our solution

Two to three times a year, universities are faced with an enormous task: to organise thousands of exams in different faculties as efficiently as possible. This also applies to the University of Fribourg, which organises three exam sessions per year. As the only bilingual university in Switzerland, it faces an additional challenge as the exams can be done in German or French. What is more is that courses and thus also exams can be taken in five faculties at the same time. Planning an exam session with 10,000 students, 200 professors and several faculties is therefore a particularly difficult task.

Customer requirement: a uniform, perfectly integrated solution

The Faculty of Law, which was still using an outdated and non-integrated solution – certain exams were even still scheduled manually, which involved a lot of effort – has realized that exam scheduling can be improved thanks to new technologies. The solution had to be available to all faculties and meet the following requirements:

  • Reduce the number of exams per day for students (ideally not more than one exam per day).
  • Combine exams for examiners into one day to ensure as continuous a timetable as possible.
  • Observe the examiners' timetable when taking the exams.
  • Observe the space capacities for the written exams.

Considering these constraints, the solution had to make it possible to draw up a schedule that is as conflict-free as possible for each exam, all teaching staff and all students. The University’s aim was to create a solution that would enable all faculties to schedule their exams consistently and intelligently. It also had to be able to be integrated into the new IS.

Use of a powerful open-source library

Trivadis recommended that the University of Fribourg adapt an open-source solution (CPSolver) to its needs. Purdue University (USA) has been using such a solution for over ten years, thanks to which it can schedule around 120,000 exams per session, for example. The solution works with operations research artificial intelligence and evaluates thousands of possible schedules to generate the most optimal one. This open-source solution has been adapted to the needs of the University of Freiburg in order to meet its technical requirements.

With the solution, exam sessions can be scheduled with just one click. Thanks to a modern algorithm, the whole process of exam scheduling is now smarter and more efficient than in the past. What’s more is that the solution is perfectly integrated into the existing IT environment and meets the requirements of the various faculties. It is also open to all faculties.

Once the data is ready, one click is all it takes and within a few seconds we get an optimal schedule of written and oral exams, all without having to leave our administration application. Despite all the constraints (timetables, conflicts, room size), the engine is so fast that we can run the calculation several times to choose the most suitable result for us.

Faculty of Law, University of Fribourg

On the verge for a full integration with Microsoft Teams and Office 365

The next step would be to integrate the smart scheduling into Microsoft Teams for Education, providing both the students and the professors a powerful and seamless user experience to interact, prepare and pass exams. In a time where university teaching increasingly takes place online, this solution provides the necessary missing piece to facilitate life and work as a matter of course.

Technologies used

  • Open-Source Library (CPSolver)
  • Operations research AI

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