irace: Iterated Racing for Automatic Algorithm Configuration

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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. Manuel López-Ibáñez. The irace software package: A tutorial. COMEX Workshop on Practical Automatic Algorithm Configuration, 2014.
    [ workshop webpage | PDF ]


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.

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 brew the R formula from the science tap (unfortunately it does not come already bottled so you need to have Xcode installed to compile it):

    $ brew tap homebrew/science
    $ brew install r

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.

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
  2. 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> system.file(package="irace")
    [1] "~/R/irace"

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=~/R/irace/ # Path given by system.file(package="irace")
    export PATH=${IRACE_HOME}/bin/:$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


If the installation directory of irace is C:/R/irace/, you can invoke irace by opening a terminal (launch the program cmd.exe) and executing:

    C:\> C:\R\irace\bin\irace.bat --help

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

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


  1. Create a directory for storing the tuning scenario setup

        $ mkdir ~/tuning
        $ cd ~/tuning
  2. Copy the template and example files to the scenario directory

        $ cp $IRACE_HOME/templates/*.tmpl .

    where $IRACE_HOME is the path to the installation directory of irace. It can be obtained by doing:

        $ R
        > library(irace)
        > system.file(package="irace")
  1. For each template in your tuning directory, remove the .tmpl suffix, and modify them following the instructions in 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.tmpl and instances-list.tmpl 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.

Frequently Asked Questions

The user guide contains a list of frequently asked questions.