@inproceedings{5287ec90442e40e8815c8f5c73c2ef8e,
title = "Benchmarking the (1+1)-CMA-ES on the BBOB-2009 noisy testbed",
abstract = "We benchmark an independent-restart-(1+1)-CMA-ES on the BBOB-2009 noisy testbed. The (1+1)-CMA-ES is an adaptive stochastic algorithm for the optimization of objective functions defined on a continuous search space in a black-box scenario. The maximum number of function evaluations used here equals 104 times the dimension of the search space. The algorithm could only solve \$4\$ functions with moderate noise in 5-D and 2 functions in 20-D.",
keywords = "CMA-ES, benchmarking, black-box optimization, evolutionary computation",
author = "Anne Auger and Nikolaus Hansen",
note = "Publisher Copyright: {\textcopyright} 2009 ACM.; 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009 ; Conference date: 08-07-2009 Through 12-07-2009",
year = "2009",
month = jan,
day = "1",
doi = "10.1145/1570256.1570345",
language = "English",
isbn = "9781605583259",
series = "Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009",
publisher = "Association for Computing Machinery",
pages = "2467--2471",
booktitle = "Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009",
}