benchmarkfcns.wayburnseadern2

benchmarkfcns.wayburnseadern2(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 Wayburn-Seader N. 2 benchmark function. SCORES = wayburnseadern2(X) computes the value of the Wayburn-Seader N. 2 function at point X. wayburnseadern2 accepts a matrix of size M-by-2 and returns a vector SCORES of size M-by-1 in which each row contains the function value for the corresponding row of X. Properties:

  • Global minimum: 0

  • Location of global minima: There are 2 global minima:(0.200139, 1), (0.424861, 1)

  • Number of dimensions: 2 (x_1, x_2)

  • Recommended domain: x_1, x_2 ∈ [-500, 500] (though often visualized in [-5, 5]^2)

  • Number of local minima: 0 (It is generally considered unimodal/bimodal

    depending on the range, but the global minima are the only real sinks)

  • Number of global minima: 2

  • Convexity: Non-convex

  • Separability: Non-separable

  • Modality: Bimodal

  • Symmetry: Symmetric

  • Differentiable: Yes

Mathematical Definition

Visualization

wayburnseadern2 landscape