IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics
Hao Wang, Diederick Vermetten, Furong Ye, Carola Doerr, Thomas B\"ack

TL;DR
IOHanalyzer is a comprehensive, user-friendly platform in R and C++ for detailed analysis, comparison, and visualization of iterative optimization heuristics' performance data, streamlining benchmarking processes.
Contribution
It introduces a flexible, interactive tool that simplifies performance analysis of IOHs and integrates with major benchmarking platforms, enhancing research efficiency.
Findings
Provides detailed statistics on fixed-target and fixed-budget performance.
Enables aggregation of performance data across multiple benchmarks.
Supports dynamic analysis of algorithm state parameters.
Abstract
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…
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Taxonomy
TopicsAdvanced Multi-Objective Optimization Algorithms · Metaheuristic Optimization Algorithms Research · Advanced Bandit Algorithms Research
