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Conference Papers Year : 2009

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 $10^{4}$ 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.
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inria-00430518 , version 1 (08-11-2009)


  • HAL Id : inria-00430518 , version 1


Anne Auger, Nikolaus Hansen. Benchmarking the (1+1)-CMA-ES on the BBOB-2009 Noisy Testbed. ACM-GECCO Genetic and Evolutionary Computation Conference, Jul 2009, Montreal, Canada. ⟨inria-00430518⟩
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