benchmarkfcns.griewank

benchmarkfcns.griewank(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 Griewank benchmark function. SCORES = griewank(X) computes the value of the Griewank’s function at point X. griewank 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: (0, 0, …, 0)

  • Number of dimensions: n (Scalable)

  • Recommended domain: x_i ∈ [-600, 600]

  • Number of local minima: Thousands (The number increases with the search area)

  • Number of global minima: 1

  • Convexity: Non-convex

  • Separability: Non-separable

  • Modality: Highly Multimodal

  • Symmetry: Symmetric

  • Differentiable: Yes

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

Mathematical Definition

Visualization

griewank landscape