Name
Title | ||
|---|---|---|
COCO: The Large Scale Black-Box Optimization Benchmarking (bbob-largescale) Test Suite. |
Abstract | ||
|---|---|---|
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. |
Year | Venue | DocType |
|---|---|---|
2019 | arXiv: Optimization and Control | Journal |
Volume | Citations | PageRank |
abs/1903.06396 | 0 | 0.34 |
References | Authors | |
4 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ouassim Ait Elhara | 1 | 10 | 1.87 |
| Konstantinos Varelas | 2 | 0 | 1.01 |
| Duc Manh Nguyen | 3 | 17 | 4.24 |
| Tea Tusar | 4 | 181 | 19.91 |
| Dimo Brockhoff | 5 | 948 | 53.97 |
| Nikolaus Hansen | 6 | 723 | 51.44 |
| Anne Auger | 7 | 1198 | 77.81 |