Alternative restart strategies for CMA-ES

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7491 LNCS, Issue PART 1, 2012, Pages 296-305

  Loshchilov, Ilya ^a,b   Schoenauer, Marc ^a,b   Sebag, Michèle ^a,b  

^a INRIA SACLAY   (France)

^b Laboratoire Interdisciplinaire des Sciences du Numérique   (France)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL BUDGET; MULTI-MODAL; POPULATION SIZES; REAL-WORLD PROBLEM; RESTART STRATEGY; SPACECRAFT TRAJECTORIES; STEP SIZE;

ARTIFICIAL INTELLIGENCE;

POPULATION STATISTICS;

EID: 84866362630     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-32937-1_30     Document Type: Conference Paper

References (16)

1. Addis, B., Cassioli, A., Locatelli, M., Schoen, F.: Global optimization for the design of space trajectories. Optimization On Line, 11 (2008)
2. Auger, A., Hansen, N.: A restart CMA evolution strategy with increasing population size. In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2005), pp. 1769-1776. IEEE Press (2005)
3. García, S., Molina, D., Lozano, M., Herrera, F.: A study on the use of nonparametric tests for analyzing the evolutionary algorithms' behaviour: a case study on the CEC 2005 special session on real parameter optimization. Journal of Heuristics 15, 617-644 (2009)
4. Hansen, N.: Compilation of results on the 2005 CEC benchmark function set (May 2006)
5. Hansen, N.: Benchmarking a BI-population CMA-ES on the BBOB-2009 function testbed. In: Rothlauf, F. (ed.) GECCO Companion, pp. 2389-2396. ACM (2009)
6. Hansen, N.: References to CMA-ES applications (2009), http://www.lri.fr/~hansen/cmaapplications.pdf
7. Hansen, N., Auger, A., Finck, S., Ros, R.: Real-parameter black-box optimization benchmarking 2012: Experimental setup. Technical report, INRIA (2012)
8. Hansen, N., Finck, S., Ros, R., Auger, A.: Real-parameter black-box optimization benchmarking 2009: Noiseless functions definitions. Technical Report RR-6829, INRIA (2009) (updated, February 2010)
9. Hansen, N., Kern, S.: Evaluating the CMA Evolution Strategy on Multimodal Test Functions. In: Yao, X., Burke, E.K., Lozano, J.A., Smith, J., Merelo-Guervós, J.J., Bullinaria, J.A., Rowe, J.E., Tiňo, P., Kabán, A., Schwefel, H.-P. (eds.) PPSN 2004. LNCS, vol. 3242, pp. 282-291. Springer, Heidelberg (2004)
10. Hansen, N., Ostermeier, A.: Completely derandomized self-adaptation in evolution strategies. Evolutionary Computation 9(2), 159-195 (2001)
11. Hansen, N., Ros, R.: Benchmarking a weighted negative covariance matrix update on the BBOB-2010 noiseless testbed. In: GECCO 2010: Proceedings of the 12th Annual Conference Comp. on Genetic and Evolutionary Computation, pp. 1673-1680. ACM, New York (2010)
12. Jastrebski, G.A., Arnold, D.V.: Improving evolution strategies through active covariance matrix adaptation. In: IEEE Congress on Evolutionary Computation, CEC 2006, pp. 2814-2821 (2006)
13. Loshchilov, I., Schoenauer, M., Sebag, M.: Black-box Optimization Benchmarking of NIPOP-aCMA-ES and NBIPOP-aCMA-ES on the BBOB-2012 Noiseless Testbed. In: GECCO 2012: Proceedings of the 14th Annual Conference on Genetic and Evolutionary Computation. ACM (page to appear, 2012)
14. Loshchilov, I., Schoenauer, M., Sebag, M.: Self-Adaptive Surrogate-Assisted Covariance Matrix Adaptation Evolution Strategy. In: GECCO 2012 Proceedings. ACM (page to appear, 2012)
15. Stracquadanio, G., La Ferla, A., De Felice, M., Nicosia, G.: Design of robust space trajectories. In: Research and Development in Intelligent Systems XXVIII, pp. 341-354. Springer (2011)
16. Vinko, T., Izzo, D.: Global Optimisation Heuristics and Test Problems for Preliminary Spacecraft Trajectory Design. Technical Report GOHTPPSTD, European Space Agency (2008)