Timetable quality can mean the difference between effcient and wasteful use of resources, and as such, good timetables are very important for all academic institutions. Today, most timetables are produced under the assumption of a static environment and does not account for inevitable disruptions. For any academic institution, a large number of changes happen during a semester and are handled manually. The objective of this project is to conduct research in quality recovery of disrupted timetables
using advanced Operations Research (OR) methods; enabling better dynamic timetables. The end goal is the development of decision supports tools for timetable administrators, to enable them to save administrative time and create better timetables for students and educators.
HypothesisDisrupted timetables at educational institutions can be recovered using specialized
mathematical models, thus improving utilization of resources and maintaining teaching quality.