We propose a Simulated Annealing approach for the Examination Timetabling problem, in the classical uncapacitated formulation of Carter et al. (1996). Our solver is based on a novel combination of many neighborhoods and a principled tuning procedure performed on artificial training instances. The experimental results on real-world benchmarks show that our solver is able to improve upon all state-of-the-art search methods from the literature on most instances, running time being equal. In addition, we performed an ablation analysis, so as to identify the most important neighborhoods. Finally, we propose a novel dataset obtained by translating real-world instances for other examination timetabling formulations. Instances and solutions, along with our source code, are available on the web for inspection and future comparison.

在卡特等人的经典无能力公式中，我们提出了一种用于考试时间表问题的模拟退火方法。（1996）。我们的求解器基于许多邻域的新颖组合以及在人工训练实例上执行的原则性调整过程。在实际基准测试中的实验结果表明，在运行时间相同的情况下，我们的求解器可以在大多数情况下改进文献中提供的所有最新搜索方法。此外，我们进行了消融分析，以找出最重要的邻域。最后，我们提出了一个新颖的数据集，该数据集是通过将现实世界中的实例翻译为其他考试时间表项而获得的。实例和解决方案以及我们的源代码可从Web上获得，以进行检查和将来的比较。