Inside the Case
Problem
Manual timetable creation was highly time-consuming and frequently led to systemic scheduling conflicts.
Solution
- Designed an automated scheduling architecture accounting for classrooms, instructors, and time constraints.
- Implemented two calculation strategies: Genetic Algorithms and an OR-Tools solver.
- Built an API layer supporting 'what-if' scenario simulations.
- Deployed the infrastructure to AWS using GitOps practices.
Result
- Significantly reduced the manual operational workload for scheduling.
- Complex timetables are now generated within seconds.
- Enabled flexible system adaptation through reliable scenario analysis.
OR-ToolsGenetic AlgorithmsAPI
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