benchmarkfcns.bukinn2¶
- benchmarkfcns.bukinn2(arg0: Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]', 'flags.c_contiguous']) Annotated[numpy.typing.NDArray[numpy.float64], '[m, 1]']¶
Computes the value of the Bukin N. 2 benchmark function. SCORES = bukinn2(X) computes the value of the Bukin N. 2 function at point X. bukinn2 accepts a matrix of size M-by-2 and returns a vector SCORES of size M-by-1 in which each row contains the function value for the corresponding row of X. Properties:
Global minimum: 0
Location of global minimum: (-10, 0)
Number of dimensions: 2
Recommended domain: x_1 in [-15, -5], x_2 in [-3, 3]
Number of local minima: 0 (unimodal)
Number of global minima: 1
Convexity: non-convex
Separability: non-separable
Modality: unimodal
Differentiable: Yes
Mathematical Definition
Visualization