This is the benchmarking framework for Iterative Optimization Heuristics (IOHs). IOHexperimenter provides easy-to-use benchmarking functionalities, including:

  • A framework for straightforward benchmarking of any iterative optimization heuristic
  • A generic framework to generate benchmarking suite for the optimization task you’re insterested in,
  • A Pseudo-Boolean Optimization (PBO) benchmark suite, containing 23 test problems of the kind $f\colon \{0,1\}^d \rightarrow \mathbb{R}$, and
  • The integration of 24 noiseless, single-objective Black-Box Optimization Benchmarking (BBOB) functions on the continuous domain, namely $f\colon \mathbb{R}^d \rightarrow \mathbb{R}$. We directly take the C implementation of BBOB test functions from https://github.com/numbbo/coco, with some modifications to accommodate our framework.
  • Logging methods to effortlessly store benchmarking data in a format compatible with IOHanalyzer, with future support for additional data logging options

IOHexperimenter is available for:

  • C++ on GitHub
  • R, as a package on GitHub (the stabble release will be pushed to CRAN soon)
  • Python (under development)
  • Java (under development)

Prerequisite

Before installing IOHexperimenter, it is necessary to install the following dependencies:

  • C++ (tested on gcc 5.4.0)