Benchmarking a weighted negative covariance matrix update on the BBOB-2010 noiseless testbed
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Mirrored sampling and sequential selection for evolution strategies
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Mirrored sampling in evolution strategies with weighted recombination
Proceedings of the 13th annual conference on Genetic and evolutionary computation
On the effect of mirroring in the IPOP active CMA-ES on the noiseless BBOB testbed
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Bounding the population size of IPOP-CMA-ES on the noiseless BBOB testbed
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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Active Covariance Matrix Adaptation and Mirrored Mutations have been independently proposed as improved variants of the well-known optimization algorithm Covariance Matrix Adaptation Evolution Strategy (CMA-ES) for numerical optimization. This paper investigates the impact of the algorithm's population size when both active covariance matrix adaptation and mirrored mutation are used in the CMA-ES. To this end, we compare the CMA-ES with standard population size λ, i.e., λ = 4 + ⌊ 3 log(D) ⌋ with a version with half this population size where D is the problem dimension.