benchmarkfcns.shubert

benchmarkfcns.shubert(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 Shubert function. SCORES = shubert(X) computes the value of the Shubert function at point X. shubert 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: approx -186.7309 (for n=2)

  • Location of global minimum: multiple

  • Number of dimensions: n

  • Recommended domain: [-10, 10]^n

  • Number of local minima: many

  • Number of global minima: multiple

  • Convexity: non-convex

  • Separability: non-separable

  • Modality: multimodal

  • Symmetry: symmetric

  • Differentiable: Yes

For more information, please visit: benchmarkfcns.info/doc/shubertfcn

Mathematical Definition

Visualization

shubert landscape