benchmarkfcns.chichinadze

benchmarkfcns.chichinadze(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 Chichinadze benchmark function. SCORES = chichinadze(X) computes the value of the Chichinadze function at point X. chichinadze 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: -43.3159 (approximately)

  • Location of global minimum: (5.90133, 0.5)

  • Number of dimensions: 2

  • Recommended domain: [-30, 30]^2

  • Number of local minima: many

  • Number of global minima: 1

  • Convexity: non-convex

  • Separability: separable

  • Modality: multimodal

  • Symmetry: non-symmetric

  • Differentiable: Yes

Mathematical Definition

Visualization

chichinadze landscape