benchmarkfcns.meyer

benchmarkfcns.meyer(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 Meyer (Meyer-Roth) benchmark function. SCORES = meyer(X) computes the value of the function at point X. meyer accepts a matrix of size M-by-3 and returns a vector SCORES of size M-by-1. Properties:

  • Global minimum: ~0.4e-4

  • Location of global minimum: (3.13, 15.16, 0.78)

  • Number of dimensions: 3

  • Recommended domain: [0, 20]^3

  • Modality: Multimodal

Mathematical Definition

\[f(x_1, x_2, x_3) = \sum_{i=1}^{5} \left[ \frac{x_1 x_3 t_i}{1 + x_1 t_i + x_2 v_i} - y_i \right]^2\]

text{where } t_i, v_i, text{ and } y_i text{ are given in Table 1.}

Visualization

No visualization available for this function.