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, 2009.
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A. Auger and N. Hansen, Performance Evaluation of an Advanced Local Search Evolutionary Algorithm, 2005 IEEE Congress on Evolutionary Computation, pp.1777-1784, 2005.
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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, 2009.
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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, 2009.
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P. A. Bosman, J. Grahl, and D. Thierens, AMaLGaM IDEAs in noiseless black-box optimization benchmarking, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2247-2254, 2009.
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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, 2009.
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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, 2009.
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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, 2009.
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M. El-abd and M. S. Kamel, Black-box optimization benchmarking for noiseless function testbed using PSO Bounds, Rothlauf, pp.2275-2280, 2009.

S. Finck, N. Hansen, R. Ros, and A. Auger, Real-parameter black-box optimization benchmarking, 2009.
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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, 2009.
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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, 2009.
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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, 2009.
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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, 2009.
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N. Hansen, A. Auger, S. Finck, and R. Ros, Real-parameter black-box optimization benchmarking 2009: Experimental setup, 2009.
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N. Hansen, S. Finck, R. Ros, and A. Auger, Real-parameter black-box optimization benchmarking 2009: Noiseless functions definitions, 2009.
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G. S. Hornby, The age-layered population structure (ALPS) evolutionary algorithm, 2009.

G. S. Hornby, Steady-state ALPS for real-valued problems, Proceedings of the 11th Annual conference on Genetic and evolutionary computation, GECCO '09, pp.795-802, 2009.
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W. Huyer and A. Neumaier, Benchmarking of MCS on the noiseless function testbed

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, 2009.
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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, 2009.
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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, pp.2255-2262, 2009.

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, 2009.
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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, 2009.
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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, 2009.
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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, 2009.
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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, 2009.
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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, 2009.
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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, 2009.
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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, 2009.
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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, 2009.
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URL : https://hal.archives-ouvertes.fr/inria-00377082

F. Rothlauf, APPENDIX Used Acronyms GA/EA: Genetic Algorithm / Evolutionary Algorithm EDA: Estimation of Distribution Algorithm CMA: Covariance Matrix Adaptation ES: Evolution Strategy PSO: Particle Swarm Optimization Algorithms ALPS-GA: Age-Layered Population, Proceedings, vol.18, 2009.

I. Amalgam, Adapted Maximum-Likelihood Gaussian Model Iterated Density Estimation Algorithm with no-improvement stretch, anticipated mean shift and interlaced restarts with one large or several small populations [5] iAMaLGaM IDEA: with incremental model building

. Lsfminbnd, Axis-parallel line search with MATLAB fminbnd univariate search

. Lsstep, Axis-parallel line search with the univariate STEP Select The Easiest Point, based on interval division