COCO: Performance Assessment. ArXiv e-prints, 2016. ,
Comparing results of 31 algorithms from the black-box optimization benchmarking BBOB-2009, Proceedings of the 12th annual conference comp on Genetic and evolutionary computation, GECCO '10, pp.1689-1696, 2010. ,
DOI : 10.1145/1830761.1830790
URL : https://hal.archives-ouvertes.fr/hal-00545727
Real-parameter black-box optimization benchmarking 2009: Noiseless functions definitions, 2009. ,
Real-Parameter Black-Box Optimization Benchmarking 2009: Noisy Functions Definitions, 2009. ,
COCO: The Experimental Procedure, ArXiv e-prints, 2016. ,
Matplotlib: A 2D Graphics Environment, Computing in Science & Engineering, vol.9, issue.3, pp.90-95, 2007. ,
DOI : 10.1109/MCSE.2007.55
An introduction to the bootstrap, 1994. ,
DOI : 10.1007/978-1-4899-4541-9
A parameter-less genetic algorithm, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pp.258-265, 1999. ,
Evaluating Las Vegas algorithms: pitfalls and remedies, Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI-98), pp.238-245, 1998. ,
Benchmarking Derivative-Free Optimization Algorithms, SIAM Journal on Optimization, vol.20, issue.1, pp.172-191, 2009. ,
DOI : 10.1137/080724083
Benchmarking optimization software with performance profiles, Mathematical Programming, vol.91, issue.2, pp.201-213, 2002. ,
DOI : 10.1007/s101070100263
On the Theory of Scales of Measurement, Science, vol.103, issue.2684, pp.677-680, 1946. ,
DOI : 10.1126/science.103.2684.677
COCO: The Bi-objective Black Box Optimization Benchmarking (bbob-biobj) Test Suite, ArXiv e-prints, 2016. ,
Evaluating evolutionary algorithms, Artificial Intelligence, vol.85, issue.1-2, pp.245-276, 1996. ,
DOI : 10.1016/0004-3702(95)00124-7