benchmarkfcns.boxbetts

benchmarkfcns.boxbetts(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 Box-Betts Quadratic Sum benchmark function. SCORES = boxbetts(X) computes the value of the Box-Betts function at point X. boxbetts accepts a matrix of size M-by-3 and returns a vector SCORES of size M-by-1. Properties:

  • Global minimum: 0

  • Location of global minimum: (1, 10, 1)

  • Number of dimensions: 3

  • Recommended domain: [0.9, 1.2] x [9, 11.2] x [0.9, 1.2]

  • Modality: multimodal

Mathematical Definition

Visualization

boxbetts landscape