benchmarkfcns.multiobjective.dtlz7¶
- benchmarkfcns.multiobjective.dtlz7(x: Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]', 'flags.c_contiguous'], num_objectives: SupportsInt | SupportsIndex = 3) Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]']¶
Computes the value of the DTLZ7 multi-objective benchmark function. SCORES = multiobjective.dtlz7(X, num_objectives) computes the value of the DTLZ7 function at point X. multiobjective.dtlz7 accepts a matrix of size M-by-N and returns a matrix SCORES of size M-by-K where K is the number of objectives. Properties:
Global Pareto front: Disconnected (2^(M-1) regions)
Number of dimensions: n (usually 20)
Recommended domain: [0, 1]^n
Modality: multimodal (disconnected front)
For more information, please visit: benchmarkfcns.info/doc/dtlz7fcn
Mathematical Definition
Visualization