benchmarkfcns.discus¶
- benchmarkfcns.discus(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 Discus benchmark function. SCORES = discus(X) computes the value of the Discus function at point X. discus accepts a matrix of size M-by-N and returns a vetor 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
Recommended domain: [-100, 100]^n
Modality: unimodal
Characteristic: High conditioning (one sensitive direction).
Mathematical Definition
Visualization