benchmarkfcns.multifidelity.branin¶
- benchmarkfcns.multifidelity.branin(arg0: Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]', 'flags.c_contiguous']) Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]']¶
Computes the value of the multi-fidelity Branin function. SCORES = branin(X) computes the value of the Branin function at point X. multifidelity.branin accepts a matrix of size M-by-2 and returns a matrix SCORES of size M-by-2. Properties (High-fidelity):
Dimensions: 2
Recommended domain: [-5, 10] x [0, 15]
Mathematical Definition
\[\begin{aligned}\]
f_b(x_1, x_2) &= (x_2 - frac{5.1 x_1^2}{4pi^2} + frac{5x_1}{pi} - 6)^2 + 10cos(x_1)(1 - frac{1}{8pi}) + 10 \ f_{hf}(x_1, x_2) &= f_b(x_1, x_2) \ f_{lf}(x_1, x_2) &= 10.0 f_b(1.2x_1, 1.2x_2) + 5x_1 + 10x_2 end{aligned}
Visualization
No visualization available for this function.