irace: Iterated Racing for Automatic Algorithm Configuration

CRAN Status CRAN Downloads R build status Codecov test coverage

[ Homepage ] [ User Guide (PDF) ]

Maintainers: Manuel López-Ibáñez, Leslie Pérez Cáceres

Creators: Manuel López-Ibáñez, Jérémie Dubois-Lacoste

Contributors: Jérémie Dubois-Lacoste, Thomas Stützle, Mauro Birattari, Eric Yuan and Prasanna Balaprakash.



The irace package implements the Iterated Race method, which is a generalization of the Iterated F-race method for the automatic configuration of optimization algorithms, that is, the tuning of their parameters 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:

  1. M. López-Ibáñez, J. Dubois-Lacoste, L. Pérez Cáceres, T. Stützle, and M. Birattari. The irace package: Iterated Racing for Automatic Algorithm Configuration. Operations Research Perspectives, 3:43–58, 2016.
    [ bibtex | doi: 10.1016/j.orp.2016.09.002 ]

  2. 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.
    [ bibtex | PDF ]

  3. Thomas Stützle and Manuel López-Ibáñez. Tutorial: Automated algorithm configuration and design. GECCO ’21: Proceedings of the Genetic and Evolutionary Computation Conference Companion, July 2021. doi:10.1145/3449726.3461404


User guide

A complete user guide comes with the package. You can access it online or, after installing the irace package, invoking from R the following command:

        R> vignette("irace-package")

The following is a quick-start guide. The user guide gives more detailed instructions.

Quick Start

  1. Install R (with your favourite package manager, and see more details below).
  2. Install irace. This command works on CMD and Powershell with R added to PATH (see detailed instructions below).
    $ Rscript -e "install.packages('irace', repos='')"
  1. Add irace to path. For windows user, this step is unfortunately more involved, so please see more detailed instructions below.
    $ export PATH="$(Rscript -e "cat(paste0(system.file(package='irace', 'bin', mustWork=TRUE), ':'))" 2> /dev/null)${PATH}"

Consider adding this line to your ~/.bashrc, ~/.zshrc, or ~/.profile for it to persist between sessions.

  1. You can open the user guide with the following command. This command works on CMD and Powershell with R added to PATH (see detailed instructions below).
    $ Rscript -e "vignette('irace-package')"

Installing R

The official instructions are available at We give below a quick R installation guide that will work in most cases.


You should install R from your package manager. On a Debian/Ubuntu system it will be something like:

$ sudo apt-get install r-base

Once R is installed, you can launch R from the Terminal and from the R prompt install the irace package. See instructions below.


You can install R directly from a CRAN mirror (

Alternatively, if you use homebrew, you can just do

    $ brew install --cask r

(Using brew install r is not recommended because that will build R from source and you will not be able to use any CRAN binary, possibly resulting in annoying build failiures).

Once R is installed, you can launch R from the Terminal (or from your Applications), and from the R prompt install the irace package. See instructions below.


You can install R from a CRAN mirror ( Once R is installed, you can launch the R console and install the irace package from it. See instructions below.

In addition to using the R console, it might be very useful to add R to PATH so you can run most of the GUN/Linux shell commands without modification in CMD or Powershell. Usually, R is installed in C:\Program Files\R\R-4.1.3 (the version number depends on your installation).

You should add the following line to PATH (if you want to use the 64-bit version)

C:\Program Files\R\R-4.1.3\bin\x64

Or, if you are on a 32-bit version

C:\Program Files\R\R-4.1.3\bin\i386

Installing the irace package

There are two methods for installing the irace R package on your computer:

  1. Install within R (automatic download):
        $ R
        R> install.packages("irace")

select a mirror close to you, and test the installation with

        R> library(irace)
        R> CTRL+d
  1. Manually download the package from CRAN and invoke at the command-line:
        $ R CMD INSTALL <package>

where <package> is one of the three versions available: .tar.gz (Unix/BSD/GNU/Linux), .tgz (MacOS X), or .zip (Windows).

If the package fails to install because of insufficient permissions, you need to force a local installation by doing:

    $ mkdir ~/R
    $ R CMD INSTALL --library=~/R irace.tar.gz
    $ export R_LIBS=~/R:${R_LIBS}

Once installed, test that it is working by doing:

    $ R
    R> library(irace)
    R> cat(system.file(package="irace", "bin", mustWork=TRUE), "\n")

The last command tells you the installation directory of irace.

GNU/Linux and OS X

Save the installation directory of irace to a variable, and add it to your .bash_profile, .bashrc or .profile:

    export IRACE_HOME=/home/user/R/irace/bin/ # Path given by system.file(package="irace", "bin", mustWork=TRUE)
    export PATH=${IRACE_HOME}:$PATH
    # export R_LIBS=~/R:${R_LIBS} # Only if local installation was forced

After adding this and opening a new terminal, you should be able to invoke irace as follows:

    $ irace --help


You can find out where the irace binary is installed by running the following in Powershell or CMD:

    C:\> Rscript -e "cat(gsub('/', '\\\\', system.file(package='irace', 'bin', 'x64', mustWork=TRUE)))"

It will output a path, such as C:\Program Files\R\R-4.1.3\library\irace\bin\x64 (replace x64 with i386 if you are on a 32-bit system), which can you add to PATH.

Then running the following should work:

    C:\> irace --help

You can also launch irace by opening the R console and executing:

    R> library(irace)
    R> irace.cmdline("--help")

GitHub (Development version)

If you wish to try the development version, you can install it by executing the following commands within the R console:

    R> install.packages("devtools")
    R> devtools::install_github("MLopez-Ibanez/irace")


You can use the irace R package from Python using rpy2. An example on how to do this is the implementation of iracepy.


  1. Create a directory for storing the tuning scenario setup
        $ mkdir ~/tuning
        $ cd ~/tuning
  1. Initialize your tuning directory with template config files
        $ $IRACE_HOME/bin/irace --init
  1. Modify the generated files following the instructions found within each file. In particular,

    There are examples in $IRACE_HOME/examples/.

  2. Put the instances in ~/tuning/Instances/. In addition, you can create a file that specifies which instances from that directory should be run and which instance-specific parameters to use. See scenario.txt and instances-list.txt for examples. The command irace will not attempt to create the execution directory (execDir), so it must exist before calling irace. The default execDir is the current directory.

  3. Calling the command:

        $ cd ~/tuning/ && $IRACE_HOME/bin/irace

performs one run of Iterated Race. See the output of irace --help for additional irace parameters. Command-line parameters override the scenario setup specified in the scenario.txt file.

Many tuning runs in parallel

For executing several repetitions of irace in parallel, call the program

    $ cd ~/tuning/ && $IRACE_HOME/bin/parallel-irace N

where N is the number of repetitions. By default, the execution directory of each run of irace will be set to ./execdir-dd, where dd is a number padded with zeroes.

Be careful, parallel-irace will create these directories from scratch, deleting them first if they already exist.

Check the help of parallel-irace by running it without parameters.

Parallelize one tuning

A single run of irace can be done much faster by executing the calls to targetRunner (the runs of the algorithm being tuned) in parallel. See the user guide for the details.


irace is Copyright (C) 2010-2020 Manuel López-Ibáñez, Jérémie Dubois-Lacoste and Leslie Pérez-Cáceres.

This program is free software (software libre); you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

IMPORTANT NOTE: Please be aware that the fact that this program is released as Free Software does not excuse you from scientific propriety, which obligates you to give appropriate credit! If you write a scientific paper describing research that made substantive use of this program, it is your obligation as a scientist to (a) mention the fashion in which this software was used in the Methods section; (b) mention the algorithm in the References section. The appropriate citation is:

The irace package uses code under the GPL from the race package is Copyright (C) 2003 Mauro Birattari.

Building an irace standalone container

Thanks to Singularity, you can build a standalone container of irace using the file irace.sindef which is available in the directory inst/ in the source tarball and github repository or, after installing the irace R package, in the installation directory given by the R expression system.file(package="irace"). After installing SingularityCE, the container may be build using:

sudo singularity build irace.sindef irace.sif

and run with:

singularity run irace.sif <arguments>

Frequently Asked Questions

The user guide contains a list of frequently asked questions.