IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics

arXiv (Cornell University)

Abstract

We present IOHexperimenter, the experimentation module of the IOHprofiler project, which aims at providing an easy-to-use and highly customizable toolbox for benchmarking iterative optimization heuristics such as local search, evolutionary and genetic algorithms, Bayesian optimization techniques, etc. IOHexperimenter can be used as a stand-alone tool or as part of a benchmarking pipeline that uses other components of IOHprofiler such as IOHanalyzer, the module for interactive performance analysis and visualization. IOHexperimenter provides an efficient interface between optimization problems and their solvers while allowing for granular logging of the optimization process. These logs are fully compatible with existing tools for interactive data analysis, which significantly speeds up the deployment of a benchmarking pipeline. The main components of IOHexperimenter are the environment to build customized problem suites and the various logging options that allow users to steer the granularity of the data records.

Authors 6

1. Jacob de Nobel
2. Furong Ye Aachen

   Leiden University

   Affiliation as printed

   LIACS , Leiden University , the Netherlands

3. Diederick Vermetten Aachen

   Leiden University

   Affiliation as printed

   LIACS , Leiden University , the Netherlands

4. Hao Wang Aachen

   Leiden University

   Affiliation as printed

   LIACS , Leiden University , the Netherlands

5. Carola Doerr Aachen

   Leiden University

   Affiliation as printed

   LIACS , Leiden University , the Netherlands

6. Thomas Bäck Aachen

   Leiden University · Sorbonne Université · LIP6

   Affiliation as printed

   LIACS , Leiden University , the Netherlands

   LIP6 , Sorbonne Université , Paris , France