mlsanityData to 7 Oct 2026

COCO: The Large Scale Black-Box Optimization Benchmarking (bbob-largescale) Test Suite

arXiv 1903.06396 ↗First posted 15 Mar 2019math.OC cs.LG cs.NEcited by 12

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Abstract (arXiv)

The bbob-largescale test suite, containing 24 single-objective functions in continuous domain, extends the well-known single-objective noiseless bbob test suite, which has been used since 2009 in the BBOB workshop series, to large dimension. The core idea is to make the rotational transformations R, Q in search space that appear in the bbob test suite computationally cheaper while retaining some desired properties. This documentation presents an approach that replaces a full rotational transformation with a combination of a block-diagonal matrix and two permutation matrices in order to construct test functions whose computational and memory costs scale linearly in the dimension of the problem.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Mar 2019.

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Citing papers per year: 2022: 2; 2023: 0; 2024: 6; 2025: 3; 2026: 1.

12 papers.