by Manuel López Ibáñez, Leslie Pérez Cáceres, Jérémie Dubois-Lacoste, Mauro Birattari, Thomas Stützle
2016
| Table of Contents |
Modern optimization algorithms typically require the setting of a large number
of parameters to optimize their performance. The immediate goal of automatic
algorithm configuration is to find, automatically, the best parameter settings of
an optimizer. Ultimately, automatic algorithm configuration has the potential
to lead to new design paradigms of optimization software. The irace package
is a software package that implements a number of automatic configuration
procedures. In particular, it offers iterated racing procedures, which have been
used successfully to automatically configure various state-of-the-art algorithms.
The iterated racing procedures implemented in irace include the iterated F-race
algorithm and several extensions and improvements over the original iterated
F-race proposal. In this paper, we describe the rationale underlying the iterated
racing procedures and introduce a number of recent extensions. Among these,
we introduce a restart mechanism to avoid premature convergence, the use of
truncated sampling distributions to handle correctly parameter bounds, and an
elitist racing procedure for ensuring that the best configurations found are also
those evaluated in the higher number of training instances. We experimentally
evaluate the most recent version of irace and demonstrate with a number of
example applications the use and potential of irace, in particular, and automatic
algorithm configuration, in general.
Keywords:automatic algorithm configuration, racing, parameter tuning
| ACOTSP | SPEAR | MOACO | |
|---|---|---|---|
| Target algorithm | ACOTSP website | executable | MOACO website |
| Parameters | acotsp-parameters.txt | spear-parameters-cat.txt | moaco-parameters-full.txt |
| Target runner | target-runner | target-runner | target-runner |
| Cut off time | 20 sec. | 300 sec. | variable (see target-runner) |
| Target evaluator | - | - | target-evaluator |
| Instances | instances.tar.gz | optimum | instances.tar.gz | instances.tar.gz |
| Scenario | scenario.txt | scenario.txt | |
| Other | - | - | Hypervolume |
The version 2.0 of the irace package will be available soon in CRAN, a preliminary version can be downloaded here.
[1] López−Ibánez, M., Pérez Cáceres, L., Dubois-Lacoste, J., Birattari, M. and Stützle, T.: The irace Package:
User Guide. Technical Report TR/IRIDIA/2016-004, IRIDIA, Université Libre de Bruxelles, Belgium, (2016).
[2] Birattari, M., Yuan, Z., Balaprakash, P. and Stützle, T .: F-race and iterated F-race: An overview.. Experimental Methods for the Analysis of Optimization Algorithms, 311−336 (2010)
[3] Pérez Cáceres, L., López−Ibánez, M. and Stützle, T.: An analysis of parameters of irace In Proceedings of EvoCOP 2014 − 14th European Conference on Evolutionary Computation in Combinatorial Optimization, volume 8600 of LNCS, 37−48 (2014)