From: A comparison of mixed-variables Bayesian optimization approaches
\({\varvec{n}}_{{\varvec{c}}}\) | \({\varvec{n}}_{\varvec{d}}\) | \({\varvec{m}_{\varvec{i}}}\) | \(N_{\text {DoE}} \) | |
---|---|---|---|---|
Branin-Hoo | 1 | 1 | 4 | 16 |
Goldstein | 2 | 1 | 5 | 40 |
Hartmann | 4 | 2 | {5,4} | 160 |
Beam Bending | 2 | 1 | 12 | 96 |