IOHanalyzer: Performance Analysis for Iterative Optimization Heuristic

We propose IOHanalyzer, a new software for analyzing the empirical performance of iterative optimization heuristics (IOHs) such as local search algorithms, genetic and evolutionary algorithms, Bayesian optimization algorithms, and similar optimizers. Implemented in R and C++, IOHanalyzer is available on CRAN. It provides a platform for analyzing and visualizing the performance of IOHs on real-valued, single-objective optimization tasks. It provides detailed statistics about the fixed-target and fixed-budget running times of the benchmarked algorithms. Performance aggregation over several benchmark problems is also possible, for example in the form of empirical cumulative distribution functions. A key advantages of IOHanalyzer over exiting packages is its highly interactive design, which allows the user to specify the performance measures, ranges, and granularity that is most useful for her experiments. It is designed to analyze not only performance traces, but also the evolution of dynamic state parameters that directly influence the search behavior of the solver. IOHanalyzer can directly process performance data from the main benchmarking platforms, including the COCO platform, Nevergrad, and our own IOHexperimenter. An R programming interface is provided for users preferring to have a finer control over the implemented functionalities.