IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics

Benchmarking in Optimization: Best Practice and Open Issues

Original

Bartz-Beielstein, T., Doerr, C., Bossek, J., Chandrasekaran, S., Eftimov, T., Fischbach, A., Kerschke, P., López-Ibáñez, M., Malan, K. M., Moore, J. H., Naujoks, B., Orzechowski, P., Volz, V., Wagner, M., and Weise, T. (2020) · 2007

Earlier work this paper cites.

IOHprofiler: A benchmarking and profiling tool for iterative optimization heuristics

Original

Doerr, C., Wang, H., Ye, F., van Rijn, S., and Bäck, T. (2018) · 2018

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Nevergrad - A gradient-free optimization platform

Rapin, J. and Teytaud, O. (2018) · 2018

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Benchmarking discrete optimization heuristics with IOHprofiler

Doerr, C., Ye, F., Horesh, N., Wang, H., Shir, O. M., and Bäck, T. (2020) · 2020

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Selecting a diverse set of benchmark instances from a tunable model problem for black-box discrete optimization algorithms

Weise, T., Chen, Y., Li, X., and Wu, Z. (2020) · 2020

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Towards large scale automated algorithm design by integrating modular benchmarking frameworks

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Aziz-Alaoui, A., Doerr, C., and Dréo, J. (2021) · 2021

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Tuning as a means of assessing the benefits of new ideas in interplay with existing algorithmic modules

de Nobel, J., Vermetten, D., Wang, H., Doerr, C., and Bäck, T. (2021) · 2021

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COCO: A platform for comparing continuous optimizers in a black-box setting

Hansen, N., Auger, A., Ros, R., Mersmann, O., Tušar, T., and Brockhoff, D. (2021) · 2021

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Automated configuration of genetic algorithms by tuning for anytime performance

Original

Ye, F., Doerr, C., Wang, H., and Bäck, T. (2021) · 2021

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IOHanalyzer: Detailed performance analyses for iterative optimization heuristics

Wang, H., Vermetten, D., Ye, F., Doerr, C., and Bäck, T. (2022) · 2022

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