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Benchmarking and performance analysis play an important role in understandingthe behaviour of iterative optimization heuristics (IOHs) such as local searchalgorithms, genetic and evolutionary algorithms, Bayesian optimizationalgorithms, etc. This task, however, involves manual setup, execution, andanalysis of the experiment on an individual basis, which is laborious and canbe mitigated by a generic and well-designed platform. For this purpose, wepropose IOHanalyzer, a new user-friendly tool for the analysis, comparison, andvisualization of performance data of IOHs.  Implemented in R and C++, IOHanalyzer is fully open source. It is availableon CRAN and GitHub. IOHanalyzer provides detailed statistics about fixed-targetrunning times and about fixed-budget performance of the benchmarked algorithmswith a real-valued codomain, single-objective optimization tasks. Performanceaggregation over several benchmark problems is possible, for example in theform of empirical cumulative distribution functions. Key advantages ofIOHanalyzer over other performance analysis packages are its highly interactivedesign, which allows users to specify the performance measures, ranges, andgranularity that are most useful for their experiments, and the possibility toanalyze not only performance traces, but also the evolution of dynamic stateparameters.  IOHanalyzer can directly process performance data from the main benchmarkingplatforms, including the COCO platform, Nevergrad, the SOS platform, andIOHexperimenter. An R programming interface is provided for users preferring tohave a finer control over the implemented functionalities.

IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics