benchmarkfcns.keane

benchmarkfcns.keane(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 Keane function. SCORES = keane(X) computes the value of the Keane function at point X. keane 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: -0.6736675 (for n=2)

  • Location of global minimum: (1.393249, 0) or (0, 1.393249)

  • Number of dimensions: n

  • Recommended domain: [0, 10]^n

  • Number of local minima: Numerous (Highly rugged/bumpy)

  • Number of global minima: 2 (in the 2D version)

  • Convexity: Non-convex

  • Separability: Non-separable

  • Modality: Highly Multimodal

  • Differentiable: Yes

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

Mathematical Definition

Visualization

keane landscape