Educational Timetabling
IOLab has worked on automated timetabling since the group was founded in 2000. We develop models and algorithms for assigning lectures, examinations, and other events to times and rooms while balancing hard operational constraints with the preferences and workload of students and staff.
Our research covers local-search metaheuristics, constraint programming, hybrid methods, benchmark design, and rigorous experimental comparison. Group members have also contributed to the organization of the International Timetabling Competitions and to widely used benchmark datasets for course timetabling.
The methods developed by the group have had practical impact beyond research. EasyLocal++, our open-source framework for local-search algorithms, became the technological foundation of EasyCourse, a commercial university timetabling system developed by EasyStaff.
The same expertise extends to sports timetabling: an IOLab team placed second in the Fifth International Timetabling Competition in 2021.
Sara Ceschia
Associate Professor of Operations Research
My research interests include local search algorithms for combinatorial optimization problems in the field of logistics, healthcare, timetabling and scheduling.
Luca Di Gaspero
Associate Professor of Information Technology · Director of IOLab
Director of IOLab. He develops intelligent optimization methods and decision-support systems, from metaheuristics and hybrid algorithms to large language models.
Andrea Schaerf
Full Professor of Information Technology
Working on Optimization from an AI perspective.