## Installation

To use this package, either clone this repository from GitHub and install locally, or use the following commands to use devtools to install the package directely:

If devtools is not yet installed, please first use

install.packages('devtools')


Error messages will be shown in your R console if there is any installation issue. Now, the IOHexperimenter package can be installed and loaded using the following commands:

devtools::install_github('IOHprofiler/IOHexperimenter@R')
library('IOHexperimenter')


This will install the package and all required dependencies.

## Usage

To benchmark your algorithm, you should first create a wrapper around it which accepts an IOHproblem object as its first parameter. This object contains the following information about the current problem:

• dimension
• function_id
• instance
• fopt (if known)
• xopt (if known)
• lower bound
• upper bound
• maximization / minimization
• suite

And the following functions:

• obj_func()
• target_hit()
• set_parameters()

Several example algorithms with corresponding wrappers have been implemented in the algorithms.R file.

Once your algorithm is compatible with an IOHproblem, you can benchmark it using the benchmark_algorithm function, with as the first parameter your (wrapped) algorithm. For information about how to configure this benchmarking procedure, please refer to the internal documentation in R, accesible by using ??benchmark_algorithm.