Ubuntu g++-{10, 9, 8} MacOS clang++, g++-{9, 8} Windows MVSC-2019

Experimenter for Iterative Optimization Heuristics (IOHs), built in* C++.

IOHexperimenter provides:

Available Problem Suites:

  • BBOB (Single Objective Noiseless) (COCO)


  • StarDiscrepancy

  • PBO

  • Submodular Graph Problems


The complete API documentation, can be found here, as well as a Getting-Started guide. In addition to the documentation, some example projects can be found in the example folder of this repository.


The pip-version of IOHexperimenters python interface is available via pip. A tutorial with python in the form of a jupyter notebook can be found in the example folder of this repository. A Getting-Started guide and the full API documentation can be found here.


If you have any questions, comments or suggestions, please don’t hesitate contacting us

Our team#

When using IOHprofiler and parts thereof, please kindly cite this work as

Jacob de Nobel, Furong Ye, Diederick Vermetten, Hao Wang, Carola Doerr and Thomas Bäck, IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics, arXiv e-prints:2111.04077, 2021.

  author = {Jacob de Nobel and
               Furong Ye and
               Diederick Vermetten and
               Hao Wang and
               Carola Doerr and
               Thomas B{\"{a}}ck},
  title = {{IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics}},
  journal = {arXiv e-prints:2111.04077},
  archivePrefix = "arXiv",
  eprint = {2111.04077},
  year = 2021,
  month = Nov,
  keywords = {Computer Science - Neural and Evolutionary Computing},
  url = {}