IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristics. IOHprofiler is a new tool for analyzing and comparing iterative optimization heuristics. Given as input algorithms and problems written in C or Python, it provides as output a statistical evaluation of the algorithms’ performance by means of the distribution on the fixed-target running time and the fixed-budget function values. In addition, IOHprofiler also allows to track the evolution of algorithm parameters, making our tool particularly useful for the analysis, comparison, and design of (self-)adaptive algorithms.
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References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Hansen, Nikolaus; Auger, Anne; Ros, Raymond; Mersmann, Olaf; Tušar, Tea; Brockhoff, Dimo: COCO: a platform for comparing continuous optimizers in a black-box setting (2021)
- Antonov, Kirill; Buzdalova, Arina; Doerr, Carola: Mutation rate control in the ((1+\lambda)) evolutionary algorithm with a self-adjusting lower bound (2020)
- Hao Wang, Diederick Vermetten, Carola Doerr, Thomas Bäck: IOHanalyzer: Performance Analysis for Iterative Optimization Heuristic (2020) arXiv