Benchmarking a BI-Population CMA-ES on the BBOB-2009 Function Testbed

Nikolaus Hansen (1, 2)

1 TAO - Machine Learning and Optimisation
2 MSR - INRIA - Microsoft Research - Inria Joint Centre

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.

Domains: Machine Learning [cs.LG]

Nikolaus Hansen. Benchmarking a BI-Population CMA-ES on the BBOB-2009 Function Testbed. ACM-GECCO Genetic and Evolutionary Computation Conference, Jul 2009, Montreal, Canada. ⟨inria-00382093⟩