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
| Hi-index | 0.00 |
Mirrored mutations as well as active covariance matrix adaptation are two techniques that have been introduced into the well-known CMA-ES algorithm for numerical optimization. Here, we investigate the impact of active covariance matrix adaptation in the IPOP-CMA-ES with mirrored mutation and a small initial population size. Active covariance matrix adaptation improves the performance on 8 of the 24 benchmark functions of the noiseless BBOB test bed. The effect is the largest on the ill-conditioned functions with the largest improvement on the discus function where the expected runtime is more than halved. On the other hand, no statistically significant adverse effects can be observed.