benchmarkfcns.multifidelity.ackley¶
- benchmarkfcns.multifidelity.ackley(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 Ackley function. SCORES = ackley(X) computes the value of the Ackley function at point X. multifidelity.ackley accepts a matrix of size M-by-N and returns a matrix SCORES of size M-by-2.
Mathematical Definition
\[f(\textbf{x}) = f(x_1, ..., x_n)= -a.exp(-b\sqrt{\frac{1}{n}\sum_{i=1}^{n}x_i^2})-exp(\frac{1}{d}\sum_{i=1}^{n}cos(cx_i))+ a + exp(1)\]
Visualization
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