irace

The irace Package: Iterated Race for Automatic Algorithm Configuration. The irace package implements the iterated racing procedure, which is an extension of the Iterated F-race procedure. Its main purpose is to automatically configure optimization algorithms by finding the most appropriate settings given a set of instances of an optimization problem. It builds upon the race package by Birattari and it is implemented in R. Keywords: automatic configuration, offline tuning, parameter tuning, racing, F-race. Relevant literature: Manuel López-Ibáñez, Jérémie Dubois-Lacoste, Thomas Stützle, and Mauro Birattari. The irace package, Iterated Race for Automatic Algorithm Configuration. Technical Report TR/IRIDIA/2011-004, IRIDIA, Université libre de Bruxelles, Belgium, 2011.


References in zbMATH (referenced in 9 articles )

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  1. Bischl, Bernd; Kühn, Tobias; Szepannek, Gero: On class imbalance correction for classification algorithms in credit scoring (2016)
  2. Chivilikhin, D.S.; Ulyantsev, V.I.; Shalyto, A.A.: Modified ant colony algorithm for constructing finite state machines from execution scenarios and temporal formulas (2016)
  3. Barbosa, Eduardo Batista de Moraes; Senne, Edson Luiz França; Silva, Messias Borges: Improving the performance of metaheuristics: an approach combining response surface methodology and racing algorithms (2015)
  4. Caraffini, Fabio; Neri, Ferrante; Picinali, Lorenzo: An analysis on separability for memetic computing automatic design (2014)
  5. Lacroix, Benjamin; Molina, Daniel; Herrera, Francisco: Region based memetic algorithm for real-parameter optimisation (2014)
  6. Liao, Tianjun; Stützle, Thomas; Montes de Oca, Marco A.; Dorigo, Marco: A unified ant colony optimization algorithm for continuous optimization (2014)
  7. López-Ibáñez, Manuel; Stützle, Thomas: Automatically improving the anytime behaviour of optimisation algorithms (2014)
  8. Mascia, Franco; López-Ibáñez, Manuel; Dubois-Lacoste, Jérémie; Stützle, Thomas: Grammar-based generation of stochastic local search heuristics through automatic algorithm configuration tools (2014)
  9. Liao, Tianjun; de Oca, Marco A.Montes; Stützle, Thomas: Computational results for an automatically tuned CMA-ES with increasing population size on the CEC’05 benchmark set (2013)