Benchmarking an algorithm for expensive high-dimensional objectives on the bbob and bbob-largescale testbeds-Reference-Cited by-同舟云学术

Benchmarking an algorithm for expensive high-dimensional objectives on the bbob and bbob-largescale testbeds

Published:2022-07-09 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Genetic and Evolutionary Computation Conference Companion
language:
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Author:

Hoffman Zachary¹,Huntsman Steve¹

Affiliation:

1. Systems and Technology Research

Funder

DARPA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3520304.3534006

Reference25 articles.

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4. Ouassim Elhara , Konstantinos Varelas , Duc Nguyen , Tea Tusar , Dimo Brockhoff , Nikolaus Hansen , and Anne Auger . 2019. COCO: the large scale black-box optimization benchmarking (BBOB-largescale) test suite. arXiv preprint arXiv:1903.06396 ( 2019 ). Ouassim Elhara, Konstantinos Varelas, Duc Nguyen, Tea Tusar, Dimo Brockhoff, Nikolaus Hansen, and Anne Auger. 2019. COCO: the large scale black-box optimization benchmarking (BBOB-largescale) test suite. arXiv preprint arXiv:1903.06396 (2019).

5. S. Finck , N. Hansen , R. Ros , and A. Auger . 2009 . Real-Parameter Black-Box Optimization Benchmarking 2009: Presentation of the Noiseless Functions . Technical Report 2009/20. Research Center PPE . http://coco.lri.fr/downloads/download15.03/bbobdocfunctions.pdf Updated February 2010. S. Finck, N. Hansen, R. Ros, and A. Auger. 2009. Real-Parameter Black-Box Optimization Benchmarking 2009: Presentation of the Noiseless Functions. Technical Report 2009/20. Research Center PPE. http://coco.lri.fr/downloads/download15.03/bbobdocfunctions.pdf Updated February 2010.

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