benchmarkfcns.schwefel¶
- benchmarkfcns.schwefel(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 Schwefel benchmark function. SCORES = schwefel(X) computes the value of the Schwefel function at point X. schwefel accepts a matrix of size M-by-N 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: (420.9687, 420.9687, …, 420.9687)
Number of dimensions: n
Recommended domain: [-500, 500]^n
Number of local minima: many
Number of global minima: 1
Convexity: non-convex
Separability: separable
Modality: multimodal
Differentiable: Yes
For more information, please visit: benchmarkfcns.info/doc/schwefelfcn
Mathematical Definition
Visualization