An experimental study of adaptive capping in irace

Leslie Pérez Cáceres, Manuel López-Ibáñez, Holger Hoos, Thomas Stützle

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

26 Scopus citations


The irace package is a widely used for automatic algorithm configuration and implements various iterated racing procedures. The original irace was designed for the optimisation of the solution quality reached within a given running time, a situation frequently arising when configuring algorithms such as stochastic local search procedures. However, when applied to configuration scenarios that involve minimising the running time of a given target algorithm, irace falls short of reaching the performance of other general-purpose configuration approaches, since it tends to spend too much time evaluating poor configurations. In this article, we improve the efficacy of irace in running time minimisation by integrating an adaptive capping mechanism into irace, inspired by the one used by ParamILS. We demonstrate that the resulting iracecap reaches performance levels competitive with those of state-of-the-art algorithm configurators that have been designed to perform well on running time minimisation scenarios. We also investigate the behaviour of iracecap in detail and contrast different ways of integrating adaptive capping.

Original languageEnglish
Title of host publicationLearning and Intelligent Optimization - 11th International Conference, LION 11, Revised Selected Papers
EditorsDmitri E. Kvasov, Yaroslav D. Sergeyev, Roberto Battiti, Roberto Battiti, Dmitri E. Kvasov, Yaroslav D. Sergeyev
PublisherSpringer Verlag
Number of pages16
ISBN (Print)9783319694030
StatePublished - 2017
Externally publishedYes
Event11th International Conference on Learning and Intelligent Optimization, LION 2017 - Nizhny Novgorod, Russian Federation
Duration: 19 Jun 201721 Jun 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10556 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th International Conference on Learning and Intelligent Optimization, LION 2017
Country/TerritoryRussian Federation
CityNizhny Novgorod


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