benchmarkfcns.paviani

benchmarkfcns.paviani(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 Paviani function. SCORES = paviani(X) computes the value of the function at point X. paviani accepts a matrix of size M-by-10 and returns a vector SCORES of size M-by-1. Properties:

  • Global minimum: -45.778468

  • Location of global minimum: (9.350266, …, 9.350266)

  • Number of dimensions: 10

  • Recommended domain: [2.001, 9.999]^10

  • Modality: Multimodal

Mathematical Definition

Visualization

paviani landscape