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Conference Papers Year : 2009

Benchmarking the (1+1)-CMA-ES on the BBOB-2009 Function 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. In this paper, an independent restart version of the (1+1)-CMA-ES is implemented and benchmarked on the BBOB-2009 noise-free testbed. The maximum number of function evaluations per run is set to $10^{4}$ times the search space dimension. The algorithm solves 23, 13 and 12 of 24 functions in dimension 2, 10 and 40, respectively.
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inria-00430517 , version 1 (08-11-2009)


  • HAL Id : inria-00430517 , version 1


Anne Auger, Nikolaus Hansen. Benchmarking the (1+1)-CMA-ES on the BBOB-2009 Function Testbed. ACM-GECCO Genetic and Evolutionary Computation Conference, Jul 2009, Montreal, Canada. ⟨inria-00430517⟩
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