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

• Documentation: https://iohprofiler.github.io/IOHexperimenter
• Publication: https://arxiv.org/abs/2111.04077

IOHexperimenter provides:

• A framework to ease the benchmarking of any iterative optimization heuristic
• Pseudo-Boolean Optimization (PBO) problem set (25 pseudo-Boolean problems)
• Integration of the well-known Black-black Optimization Benchmarking (BBOB) problem set (24 continuous problems)
• W-model problem sets constructed on OneMax and LeadingOnes
• Integration of the Tree Decomposition (TD) Mk Landscapes problems
• Integration of the submodular optimization problems in Competition - Evolutionary Submodular Optimisation GECCO 2022
• Interface for adding new problems and suite/problem set
• Advanced logging module that takes care of registering the data in a seamless manner
• Data format is compatible with IOHanalyzer

C++ Interface

• Instructions regarding installation and a quickstart guide can be found on GitHub
• A full API documentation is available here

Python Interface

• pip package
• A extensive tutorial can be found in the python notebook
• A more condensed set of examples can be found here
• A full API documentation is available here