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GECCO
2009
Springer

Benchmarking the (1+1)-CMA-ES on the BBOB-2009 noisy testbed

9 years 6 months ago
Benchmarking the (1+1)-CMA-ES on the BBOB-2009 noisy testbed
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. Categories and Subject Descriptors
Anne Auger, Nikolaus Hansen
Added 24 Jul 2010
Updated 24 Jul 2010
Type Conference
Year 2009
Where GECCO
Authors Anne Auger, Nikolaus Hansen
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