# Educational Timetabling: Problems, Benchmarks, and State-of-the-Art Results

arXiv: https://arxiv.org/abs/2201.07525 · HTML: https://mlsanity.com/paper/2201.07525/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 114 references that are in the map.
- First posted on arXiv 19 Jan 2022.

## Builds on (most cited first, 2 of 2)

- [Fairness in Academic Course Timetabling](https://mlsanity.com/paper/1303.2860/) (2013)
- [Feature-based tuning of simulated annealing applied to the curriculum-based course timetabling problem](https://mlsanity.com/paper/1409.7186/) (2014)

## Built on by (most cited first, 4 of 4)

- [Large Language Models for Combinatorial Optimization: A Systematic Review](https://mlsanity.com/paper/2507.03637/) (2025)
- [Which algorithm to select in sports timetabling?](https://mlsanity.com/paper/2309.03229/) (2023)
- [Planning Courses for Student Success at the American College of Greece](https://mlsanity.com/paper/2207.02659/) (2022)
- [Qualified Educational Capacity Planning under Heterogeneous Student Support Needs: A Synthetic Benchmark and Decision-Support Framework](https://mlsanity.com/paper/2606.30650/) (2026)

## Abstract (arXiv)

We propose a survey of the research contributions on the field of Educational Timetabling with a specific focus on "standard" formulations and the corresponding benchmark instances. We identify six of such formulations and we discuss their features, pointing out their relevance and usability. Other available formulations and datasets are also reviewed and briefly discussed. Subsequently, we report the main state-of-the-art results on the selected benchmarks, in terms of solution quality (upper and lower bounds), search techniques, running times, statistical distributions, and other side settings.