Annals of Operations Research

, Volume 252, Issue 2, pp 239–254

Feature-based tuning of single-stage simulated annealing for examination timetabling

  • Michele Battistutta
  • Andrea Schaerf
  • Tommaso Urli
Article

DOI: 10.1007/s10479-015-2061-8

Cite this article as:
Battistutta, M., Schaerf, A. & Urli, T. Ann Oper Res (2017) 252: 239. doi:10.1007/s10479-015-2061-8
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Abstract

We propose a simulated annealing approach for the examination timetabling problem, as formulated in the 2nd International Timetabling Competition. We apply a single-stage procedure in which infeasible solutions are included in the search space and dealt with using suitable penalties. Upon our approach, we perform a statistically-principled experimental analysis, in order to understand the effect of parameter selection on the performance of our algorithm, and to devise a feature-based parameter tuning strategy, which can achieve better generalization on unseen instances with respect to a one-fits-all parameter setting. The outcome of this work is that this rather straightforward search method, if properly tuned, is able to compete with all state-of-the-art specialized solvers on the available instances. As a byproduct of this analysis, we propose and publish a new, larger set of (artificial) instances that could be used for tuning and also as a ground for future comparisons.

Keywords

Examination timetabling Local search Simulated annealing Metaheuristics Linear regression Feature-based parameter tuning 

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.DIEGMUniversity of UdineUdineItaly
  2. 2.Optimisation Research GroupNICTA and The Australian National UniversityCanberraAustralia

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