JAGENDA project

The university timetabling problem and its variations are a part of the larger class of timetabling and scheduling problems.

The aim in timetabling is to find an assignment of entities to a limited number of resources while satisfying all the constraints. Due to inherent problem complexity and variability, most of the real-world university timetabling problems are NP-complete. This calls for the use of heuristic algorithms that do not guarantee an optimal solution, but are in many cases able to produce a solution that is "good enough" for practical purposes.

It has been previously shown that metaheuristic-based techniques (such as evolutionary algorithms, tabu-search etc.) are especially well suited for solving these kinds of problems.

The motivation for this project emerged from a need for automated timetable generation at our faculty. The timetables could no longer be constructed using traditional methods due to the increased complexity caused by teaching curriculum reforms.

We research two different metaheuristics for timetable construction:

• genetic algorithm (GA)
  
• ant colony optimization (ACO).