benchmarkfcns.tablefcn

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

  • Global minimum: -26.920336

  • Location of global minimum: (+/- 9.6461, +/- 9.6461)

  • Number of dimensions: 2

  • Recommended domain: [-10, 10]^2

  • Modality: multimodal

Mathematical Definition

Visualization

tablefcn landscape