benchmarkfcns.goldsteinprice

benchmarkfcns.goldsteinprice(arg0: Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]', 'flags.c_contiguous']) → Annotated[numpy.typing.NDArray[numpy.float64], '[m, 1]']

Computes the value of Goldstein-Price benchmark function. SCORES = goldsteinprice(X) computes the value of the Goldstein-Price function at point X. goldsteinprice 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: 3

  • Location of global minimum: (0, -1)

  • Number of dimensions: 2

  • Recommended domain: [-2, 2]^2

  • Number of local minima: 4

  • Number of global minima: 1

  • Convexity: Non-convex

  • Separability: Non-separable

  • Modality: Multimodal

  • Symmetry: Non-symmetric

  • Differentiable: Yes

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

Mathematical Definition

Visualization

goldsteinprice landscape