A. Auger, Benchmarking the (1+1) evolution strategy with one-fifth success rule on the BBOB-2009 function testbed, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2447-2452
DOI : 10.1145/1570256.1570342

URL : https://hal.archives-ouvertes.fr/inria-00430515

A. Auger and N. Hansen, Benchmarking the (1+1)-CMA-ES on the BBOB-2009 function testbed, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2459-2466
DOI : 10.1145/1570256.1570344

URL : https://hal.archives-ouvertes.fr/inria-00430517

A. Auger and R. Ros, Benchmarking the pure random search on the BBOB-2009 testbed, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2479-2484
DOI : 10.1145/1570256.1570347

URL : https://hal.archives-ouvertes.fr/inria-00430532

A. N. Peter, J. Bosman, D. Grahl, and . Thierens, AMaLGaM IDEAs in noiseless black-box optimization benchmarking, Rothlauf [32], pp.2247-2254

B. Doerr, M. Fouz, M. Schmidt, and M. Wahlström, BBOB, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2239-2246
DOI : 10.1145/1570256.1570312

M. El-abd and M. S. Kamel, Black-box optimization benchmarking for noiseless function testbed using an EDA and PSO hybrid, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2263-2268
DOI : 10.1145/1570256.1570315

M. El-abd and M. S. Kamel, Black-box optimization benchmarking for noiseless function testbed using particle swarm optimization, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2269-2274
DOI : 10.1145/1570256.1570316

M. El-abd and M. S. Kamel, Black-box optimization benchmarking for noiseless function testbed using PSO Bounds, Rothlauf [32], pp.2275-2280

S. Finck, N. Hansen, R. Ros, and A. Auger, Real-parameter black-box optimization benchmarking 2009: Presentation of the noiseless functions, 2009.

M. Gallagher, Black-box optimization benchmarking, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2281-2286
DOI : 10.1145/1570256.1570318

C. García-martínez and M. Lozano, A continuous variable neighbourhood search based on specialised EAs, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2287-2294
DOI : 10.1145/1570256.1570319

J. García-nieto, E. Alba, and J. Apolloni, Noiseless functions black-box optimization, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2231-2238
DOI : 10.1145/1570256.1570311

N. Hansen, A. Auger, S. Finck, and R. Ros, Real-parameter black-box optimization benchmarking 2009: Experimental setup, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00362649

N. Hansen, S. Finck, R. Ros, and A. Auger, Real-parameter black-box optimization benchmarking 2009: Noiseless functions definitions, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00362633

N. Hansen, Benchmarking a BI-population CMA-ES on the BBOB-2009 function testbed, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2389-2396
DOI : 10.1145/1570256.1570333

URL : https://hal.archives-ouvertes.fr/inria-00382093

N. Hansen, Benchmarking the nelder-mead downhill simplex algorithm with many local restarts, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2403-2408
DOI : 10.1145/1570256.1570335

URL : https://hal.archives-ouvertes.fr/inria-00382104

G. S. Hornby, The age-layered popu- lation structure (ALPS) evolutionary algorithm. http://coco.gforge.inria.fr/doku.php?id=bbob-2009-results Noiseless testbed. [18] Waltraud Huyer and Arnold Neumaier. Bench- marking of MCS on the noiseless function testbed, 2009.

P. Korosec and J. Silc, A stigmergy-based algorithm for black-box optimization, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2295-2302
DOI : 10.1145/1570256.1570320

J. Kubalik, Black-box optimization benchmarking of prototype optimization with evolved improvement steps for noiseless function testbed, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2303-2308
DOI : 10.1145/1570256.1570321

D. Molina, M. Lozano, and F. Herrera, A memetic algorithm using local search chaining for black-box optimization benchmarking 2009 for noise free functions, Rothlauf [32], pp.2255-2262

M. Nicolau, Application of a simple binary genetic algorithm to a noiseless testbed benchmark, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2473-2478
DOI : 10.1145/1570256.1570346

URL : https://hal.archives-ouvertes.fr/inria-00377093

L. Pál, T. Csendes, M. C. Markót, and A. Neumaier, BBO-benchmarking of the GLOBAL method for the noiseless function testbed

P. Po?ík, BBOB-benchmarking a simple estimation of distribution algorithm with cauchy distribution, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2309-2314
DOI : 10.1145/1570256.1570322

P. Po?ík, BBOB-benchmarking the DIRECT global optimization algorithm, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2315-2320
DOI : 10.1145/1570256.1570323

P. Po?ík, BBOB-benchmarking the generalized generation gap model with parent centric crossover, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2321-2328
DOI : 10.1145/1570256.1570324

P. Po?ík, BBOB-benchmarking the Rosenbrock's local search algorithm, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2337-2342
DOI : 10.1145/1570256.1570326

P. Po?ík, BBOB-benchmarking two variants of the line-search algorithm, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2329-2336
DOI : 10.1145/1570256.1570325

R. Ros, Benchmarking sep-CMA-ES on the BBOB-2009 function testbed, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2435-2440
DOI : 10.1145/1570256.1570340

URL : https://hal.archives-ouvertes.fr/inria-00377087

R. Ros, Benchmarking the BFGS algorithm on the BBOB-2009 function testbed, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2409-2414
DOI : 10.1145/1570256.1570336

URL : https://hal.archives-ouvertes.fr/inria-00377076

R. Ros, Benchmarking the NEWUOA on the BBOB-2009 function testbed, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2421-2428
DOI : 10.1145/1570256.1570338

URL : https://hal.archives-ouvertes.fr/inria-00377082