论文信息 - Benchmarking a BI-population CMA-ES on the BBOB-2009 function testbed

Benchmarking a BI-population CMA-ES on the BBOB-2009 function testbed

We propose a multistart CMA-ES with equal budgets for two interlaced restart strategies, one with an increasing population size and one with varying small population sizes. This BI-population CMA-ES is benchmarked on the BBOB-2009 noiseless function testbed and could solve 23, 22 and 20 functions out of 24 in search space dimensions 10, 20 and 40, respectively, within a budget of less than $10^6 D$ function evaluations per trial.

Nikolaus Hansen | N. Hansen

[1] Raymond Ros,et al. Real-Parameter Black-Box Optimization Benchmarking 2009: Experimental Setup , 2009 .

[2] Petros Koumoutsakos,et al. Reducing the Time Complexity of the Derandomized Evolution Strategy with Covariance Matrix Adaptation (CMA-ES) , 2003, Evolutionary Computation.

[3] Petros Koumoutsakos,et al. A Method for Handling Uncertainty in Evolutionary Optimization With an Application to Feedback Control of Combustion , 2009, IEEE Transactions on Evolutionary Computation.

[4] Nikolaus Hansen,et al. The CMA Evolution Strategy: A Comparing Review , 2006, Towards a New Evolutionary Computation.

[5] Nikolaus Hansen,et al. Evaluating the CMA Evolution Strategy on Multimodal Test Functions , 2004, PPSN.

[6] Anne Auger,et al. Real-Parameter Black-Box Optimization Benchmarking 2009: Noiseless Functions Definitions , 2009 .

[7] Nikolaus Hansen,et al. Completely Derandomized Self-Adaptation in Evolution Strategies , 2001, Evolutionary Computation.

[8] Nikolaus Hansen,et al. A restart CMA evolution strategy with increasing population size , 2005, 2005 IEEE Congress on Evolutionary Computation.