benchmarkfcns.damavandi

benchmarkfcns.damavandi(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 Damavandi benchmark function. SCORES = damavandi(X) computes the value of the Damavandi function at point X. damavandi accepts a matrix of size M-by-2 and returns a vector SCORES of size M-by-1. Properties:

  • Global minimum: 0

  • Location of global minimum: (2, 2)

  • Number of dimensions: 2

  • Recommended domain: [0, 14]^2

  • Modality: multimodal

Mathematical Definition

Visualization

damavandi landscape