  Benchmarking and performance analysis play an important role in understanding
the behaviour of iterative optimization heuristics (IOHs) such as local search
algorithms, genetic and evolutionary algorithms, Bayesian optimization
algorithms, etc. This task, however, involves manual setup, execution, and
analysis of the experiment on an individual basis, which is laborious and can
be mitigated by a generic and well-designed platform. For this purpose, we
propose IOHanalyzer, a new user-friendly tool for the analysis, comparison, and
visualization of performance data of IOHs.
  Implemented in R and C++, IOHanalyzer is fully open source. It is available
on CRAN and GitHub. IOHanalyzer provides detailed statistics about fixed-target
running times and about fixed-budget performance of the benchmarked algorithms
with a real-valued codomain, single-objective optimization tasks. Performance
aggregation over several benchmark problems is possible, for example in the
form of empirical cumulative distribution functions. Key advantages of
IOHanalyzer over other performance analysis packages are its highly interactive
design, which allows users to specify the performance measures, ranges, and
granularity that are most useful for their experiments, and the possibility to
analyze not only performance traces, but also the evolution of dynamic state
parameters.
  IOHanalyzer can directly process performance data from the main benchmarking
platforms, including the COCO platform, Nevergrad, the SOS platform, and
IOHexperimenter. An R programming interface is provided for users preferring to
have a finer control over the implemented functionalities.
