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

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.

Anne Auger | Nikolaus Hansen | N. Hansen | A. Auger

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