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Benchmarking sep-CMA-ES on the BBOB-2009 function testbed

Raymond Ros
2009 Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference - GECCO '09  
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doi:10.1145/1570256.1570340 dblp:conf/gecco/Ros09d fatcat:ltyuoyavdba6fntywaa4nsb7h4

Benchmarking sep-CMA-ES on the BBOB-2009 noisy testbed

Raymond Ros
2009 Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference - GECCO '09  
A partly time and space linear CMA-ES is benchmarked on the BBOB-2009 noisy function testbed.  ...  This algorithm with a multistart strategy with increasing population size solves 10 functions out of 30 in 20-D.  ...  A mixed strategy of using sep-CMA-ES and CMA-ES is proposed here and benchmarked on a noisy function testbed.  ... 
doi:10.1145/1570256.1570341 dblp:conf/gecco/Ros09e fatcat:xz7uxw3rdzblljtdjvgppslmyu

Benchmarking the (1,4)-CMA-ES with mirrored sampling and sequential selection on the noisy BBOB-2010 testbed

Anne Auger, Dimo Brockhoff, Nikolaus Hansen
2010 Proceedings of the 12th annual conference comp on Genetic and evolutionary computation - GECCO '10  
In this paper, we benchmark the (1,4 s m )-CMA-ES which implements mirrored samples and sequential selection on the BBOB-2010 noisy testbed.  ...  Moreover, on 7 of the 8 functions that are solved by the (1,4 s m )-CMA-ES in 20D, we see a large improvement over the best algorithm of the BBOB-2009 benchmarking for the corresponding functions-ranging  ...  Acknowledgments This work receives support by the French national research agency (ANR) within the SYSCOMM project ANR-08-SYSC-017 and within the COSINUS project ANR-08-COSI-007-12.  ... 
doi:10.1145/1830761.1830782 dblp:conf/gecco/AugerBH10j fatcat:lqdbaumiwjho3jvpypeebxzfjy

Investigating the impact of sequential selection in the (1,4)-CMA-ES on the noisy BBOB-2010 testbed

Anne Auger, Dimo Brockhoff, Nikolaus Hansen
2010 Proceedings of the 12th annual conference comp on Genetic and evolutionary computation - GECCO '10  
This paper investigates the impact of the application of sequential selection to the (1,4)-CMA-ES on the BBOB-2010 noisy benchmark testbed.  ...  Moreover, the (1,4 s )-CMA-ES shows shorter expected running times on 6 functions of up to 32% compared to the functionwise best algorithm of the BBOB-2009 benchmarking (in 20D and for a target value of  ...  the BBOB-2009 benchmarking on 6 functions (in 20D and for a target value of 10 −7 ).  ... 
doi:10.1145/1830761.1830780 dblp:conf/gecco/AugerBH10h fatcat:iviktrh3tvfcdd4j3dp5g46agq

Comparing results of 31 algorithms from the black-box optimization benchmarking BBOB-2009

Nikolaus Hansen, Anne Auger, Raymond Ros, Steffen Finck, Petr Pošík
2010 Proceedings of the 12th annual conference comp on Genetic and evolutionary computation - GECCO '10  
This paper presents results of the BBOB-2009 benchmarking of 31 search algorithms on 24 noiseless functions in a black-box optimization scenario in continuous domain.  ...  Searching in larger dimension and multi-modal functions appears to be more difficult. The choice of the best algorithm also depends remarkably on the available budget of function evaluations.  ...  Technical Report 2009/20, Research Center PPE, 2009. [11] M. Gallagher. Black-box optimization benchmarking: results for the BayEDAcG algorithm on the noiseless function testbed.  ... 
doi:10.1145/1830761.1830790 dblp:conf/gecco/HansenARFP10 fatcat:thucs3rocfg6vmwtxfudxypqee

Permuted Orthogonal Block-Diagonal Transformation Matrices for Large Scale Optimization Benchmarking

Ouassim Ait ElHara, Anne Auger, Nikolaus Hansen
2016 Proceedings of the 2016 on Genetic and Evolutionary Computation Conference - GECCO '16  
We investigate the impact of the different parameters of the transformation on its shape and on the difficulty of the problems for separable CMA-ES.  ...  We illustrate the use of the above defined transformation in the BBOB-2009 testbed as replacement for the expensive orthogonal (rotation) matrices.  ...  This work was supported by the grant ANR-12-MONU-0009 (NumBBO) of the French National Research Agency.  ... 
doi:10.1145/2908812.2908937 dblp:conf/gecco/ElHaraAH16 fatcat:4h6lerg4zrbctf2djodyyoh3v4

Benchmarking separable natural evolution strategies on the noiseless and noisy black-box optimization testbeds

Tom Schaul
2012 Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference companion - GECCO Companion '12  
It is thus quite similar to sep-CMA-ES [9] .  ...  This report provides the the most extensive empirical results on that algorithm to date, on both the noise-free and noisy BBOB testbeds. any type of distribution, by ascending the gradient towards higher  ...  Acknowlegements The author wants to thank the organizers of the BBOB workshop for providing such a well-designed benchmark setup, and especially such high-quality post-processing utilities.  ... 
doi:10.1145/2330784.2330815 dblp:conf/gecco/Schaul12a fatcat:snp6w5ydejcf3mxrefmztczvwm

Population-based heuristic algorithms for continuous and mixed discrete-continuous optimization problems

Tianjun Liao
2015 4OR  
(iii) we extend CMA-ES to tackle mixed discrete-continuous optimization problems.  ...  We also propose iCMAES-ILS, a hybrid algorithm that loosely couples IPOP-CMA-ES, a CMA-ES variant that uses a restart schema coupled with an increasing population iii v me to apply for a fellowship from  ...  IPOP-CMA-ES embeds CMA-ES into a restart mechanism that increases the population size between successive runs of CMA-ES.  ... 
doi:10.1007/s10288-015-0285-8 fatcat:fbdeu2lx4ngghdyqenamhfckry