Benchmarking a weighted negative covariance matrix update on the BBOB-2010 noisy testbed

Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10 - Companion Publication

Volumn , Issue , 2010, Pages 1681-1687

  Hansen, Nikolaus ^a   Ros, Raymond ^a  

^a INRIA SACLAY   (France)

Author keywords

Active CMA ES; Benchmarking; Black box optimization; CMA ES; IPOP CMA ES

Indexed keywords

ACTIVE CMA-ES; BLACK-BOX OPTIMIZATION; CMA-ES; IPOP-CMA-ES; NOISE MODELS; PERFORMANCE GAIN; PERFORMANCE LOSS; SEARCH SPACE DIMENSION; SPHERE FUNCTIONS; UNIMODAL FUNCTIONS;

BENCHMARKING; OPTIMIZATION; SPHERES; TEST FACILITIES; TESTBEDS;

COVARIANCE MATRIX;

EID: 77955953631     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1830761.1830789     Document Type: Conference Paper

References (14)

1. A. Auger and N. Hansen. A restart CMA evolution strategy with increasing population size. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2005), pages 1769-1776. IEEE Press, 2005.
2. S. Finck, N. Hansen, R. Ros, and A. Auger. Real-parameter black-box optimization benchmarking 2010: Presentation of the noisy functions. Technical Report 2009/21, Research Center PPE, 2010.
3. N. Hansen. Benchmarking a BI-population CMA-ES on the BBOB-2009 function testbed. In Rothlauf [14], pages 2389-2396.
4. N. Hansen. Benchmarking a BI-population CMA-ES on the BBOB-2009 noisy testbed. In Rothlauf [14], pages 2397-2402.
5. N. Hansen, A. Auger, S. Finck, and R. Ros. Real-parameter black-box optimization benchmarking 2010: Experimental setup. Technical Report RR-7215, INRIA, 2010.
6. N. Hansen, S. Finck, R. Ros, and A. Auger. Real-parameter black-box optimization benchmarking 2009: Noisy functions definitions. Technical Report RR-6869, INRIA, 2009. Updated February 2010.
7. N. Hansen and S. Kern. Evaluating the CMA evolution strategy on multimodal test functions. In X. Yao et al., editors, Parallel Problem Solving from Nature PPSN VIII, volume 3242 of LNCS, pages 282-291. Springer, 2004.
8. N. Hansen, S. Muller, and P. Koumoutsakos. Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES). Evolutionary Computation, 11(1):1-18, 2003.
9. N. Hansen and A. Ostermeier. Completely derandomized self-adaptation in evolution strategies. Evolutionary Computation, 9(2):159-195, 2001.
10. N. Hansen and R. Ros. Benchmarking a weighted negative covariance matrix update on the BBOB-2010 noiseless testbed. In J. Branke, editor, GECCO (Companion). ACM, 2010.
11. C. Igel, T. Suttorp, and N. Hansen. A computational efficient covariance matrix update and a (1+1)-CMA for evolution strategies. In Proceedi ngs of th e 8th annual conference on genetic and evolutionary computation GECCO, pages 453-460. ACM, 2006.
12. G. Jastrebski and D. Arnold. Improving evolution strategies through active covariance matrix adaptation. In IEEE Congress on Evolutionary Computation, CEC 2006, Proceedings, pages 2814-2821. IEEE, 2006.
13. K. Price. Differential evolution vs. the functions of the second ICEO. In Proc. of the IEEE International Congress on Evolutionary Computation, pages 153-157, 1997.
14. F. Rothlauf, editor. Genetic and Evolutionary Computation Conference, GECCO 2009, Proceedings, Montreal, Québec, Canada, July 8-12, 2009, Companion Material. ACM, 2009.