TY - GEN
T1 - Benchmarking the (1+1)-CMA-ES on the BBOB-2009 function testbed
AU - Auger, Anne
AU - Hansen, Nikolaus
N1 - Publisher Copyright:
© 2009 ACM.
PY - 2009/1/1
Y1 - 2009/1/1
N2 - 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 104 times the search space dimension. The algorithm solves 23, 13 and 12 of 24 functions in dimension 2, 10 and 40, respectively.
AB - 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 104 times the search space dimension. The algorithm solves 23, 13 and 12 of 24 functions in dimension 2, 10 and 40, respectively.
KW - Benchmarking
KW - Black-box optimization
KW - CMA-ES
KW - Evolutionary computation
U2 - 10.1145/1570256.1570344
DO - 10.1145/1570256.1570344
M3 - Conference contribution
AN - SCOPUS:77955931663
SN - 9781605583259
T3 - Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
SP - 2459
EP - 2465
BT - Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
PB - Association for Computing Machinery
T2 - 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
Y2 - 8 July 2009 through 12 July 2009
ER -