benchmarkfcns.biggsexp03¶
- benchmarkfcns.biggsexp03(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 Biggs EXP N. 03 benchmark function. SCORES = biggsexp03(X) computes the value of the Biggs EXP N. 03 function at point X. biggsexp03 accepts a matrix of size M-by-3 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 minimum: (1, 10, 1)
Number of dimensions: 3
Recommended domain: [0, 20]^3
Number of local minima: 0
Number of global minima: 1
Convexity: non-convex
Separability: non-separable
Modality: unimodal in the standard domain, but can be multimodal in larger
domains
Symmetry: non-symmetric
Differentiable: yes
Mathematical Definition
Visualization