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

\[f(\mathbf{x}) = \sum_{i=1}^{10} \left[ (\ln(x_i - 2))^2 + (\ln(10 - x_i))^2 \right] - \left( \prod_{i=1}^{10} x_i \right)^{0.2}\]

Visualization

No visualization available for this function.