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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.
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Contributor : Dimo Brockhoff Connect in order to contact the contributor
Submitted on : Tuesday, March 26, 2019 - 3:12:37 PM
Last modification on : Friday, February 4, 2022 - 3:08:38 AM
Long-term archiving on: : Thursday, June 27, 2019 - 5:00:23 PM


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  • HAL Id : hal-02068407, version 2
  • ARXIV : 1903.06396


Ouassim Ait Elhara, Konstantinos Varelas, Duc Hung Nguyen, Tea Tušar, Dimo Brockhoff, et al.. COCO: The Large Scale Black-Box Optimization Benchmarking (bbob-largescale) Test Suite. 2019. ⟨hal-02068407v2⟩



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