Feature-based tuning of simulated annealing applied to the
  curriculum-based course timetabling problem
  We consider the university course timetabling problem, which is one of the
most studied problems in educational timetabling. In particular, we focus our
attention on the formulation known as the curriculum-based course timetabling
problem, which has been tackled by many researchers and for which there are
many available benchmarks.
  The contribution of this paper is twofold. First, we propose an effective and
robust single-stage simulated annealing method for solving the problem.
Secondly, we design and apply an extensive and statistically-principled
methodology for the parameter tuning procedure. The outcome of this analysis is
a methodology for modeling the relationship between search method parameters
and instance features that allows us to set the parameters for unseen instances
on the basis of a simple inspection of the instance itself. Using this
methodology, our algorithm, despite its apparent simplicity, has been able to
achieve high quality results on a set of popular benchmarks.
  A final contribution of the paper is a novel set of real-world instances,
which could be used as a benchmark for future comparison.
