benchmarkfcns.multifidelity.schwefel

benchmarkfcns.multifidelity.schwefel(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 Schwefel function. SCORES = schwefel(X) computes the value of the Schwefel function at point X. multifidelity.schwefel accepts a matrix of size M-by-N and returns a matrix SCORES of size M-by-2.

Mathematical Definition

\[f(\textbf{x}) = f(x_1, x_2, ..., x_n) = 418.9829d -{\sum_{i=1}^{n} x_i sin(\sqrt{|x_i|})}\]

Visualization