This thesis investigates improving the group project matching algorithm of TU Delft's Project Forum platform. We formalize the matching problem as a many-to-one, one-sided matching with group formation, where students have preferences over project topics and may wish to pregroup with peers.

We implement and evaluate two mechanisms: Chiarandini – a mechanism reimplemented from the literature and adapted to our grouping setting – and our novel Fair mechanism which incorporates additional fairness considerations for pregrouping. Both use mixed integer linear programming. Leximin is selected as the objective function. These two mechanisms are compared to our previous mechanism, BEPSys, which matches greedily determined groups of students to projects using an optimal algorithm.

Our evaluation uses historical instances from TU Delft and SDU as well as synthetic instances that we generate. Results show that both new mechanisms significantly outperform the prior BEPSys algorithm, both in terms of quality of results and runtime. Our novel Fair mechanism successfully allows pregrouping without disadvantaging solo students, although sometimes at significant cost to pregrouping students. The leximin objective, implemented using an ordered weighted averaging function, is shown to not work optimally in some tested instances.