Configuring irace using surrogate configuration benchmarks

Nguyen Dang, Patrick De Causmaecker, LESLIE ANGELICA PEREZ CACERES, Thomas Stützle

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

7 Scopus citations

Abstract

Over the recent years, several tools for the automated configuration of parameterized algorithms have been developed. These tools, also called configurators, have themselves parameters that influence their search behavior and make them malleable to different kinds of configuration tasks. The default values of these parameters are set manually based on the experience of the configurator's developers. Studying the impact of these parameters or coniguring them is very expensive as it would require many executions of these tools on coniguration tasks, each taking often many hours or days of computation. In this work, we tackle this problem using a metatuning process, based on the use of surrogate benchmarks that are much faster to evaluate. This paper studies the feasibility of this process using the popular irace configurator as the method to be meta-configured. We first study the consistency between the real and surrogate benchmarks using three measures: the prediction accuracy of the surrogate models, the homogeneity of the benchmarks and the list of important algorithm parameters. Afterwards, we use irace to configure irace on those surrogates. Experimental results indicate the feasibility of this process and a clear potential improvement of irace over its default configuration.

Original languageEnglish
Title of host publicationGECCO 2017 - Proceedings of the 2017 Genetic and Evolutionary Computation Conference
PublisherAssociation for Computing Machinery, Inc
Pages243-250
Number of pages8
ISBN (Electronic)9781450349208
DOIs
StatePublished - 1 Jul 2017
Event2017 Genetic and Evolutionary Computation Conference, GECCO 2017 - Berlin, Germany
Duration: 15 Jul 201719 Jul 2017

Publication series

NameGECCO 2017 - Proceedings of the 2017 Genetic and Evolutionary Computation Conference

Conference

Conference2017 Genetic and Evolutionary Computation Conference, GECCO 2017
CountryGermany
CityBerlin
Period15/07/1719/07/17

Keywords

  • Automated parameter configuration
  • Surrogate benchmarks

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