benchmarkfcns.multiobjective.cf9

benchmarkfcns.multiobjective.cf9(x: Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]', 'flags.c_contiguous'], return_constraints: bool = False) → Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]']

Computes the value of the CEC 2009 CF9 constrained multi-objective benchmark function. SCORES = multiobjective.cf9(X) computes the value of the CF9 function at point X. multiobjective.cf9 accepts a matrix of size M-by-N and returns a matrix SCORES of size M-by-3. If return_constraints is True, returns an M-by-4 matrix where the last column contains the constraint violation (values > 0 are violations). Properties:

  • Recommended domain: x1, x2 in [0, 1], xj in [-2, 2] for j=3..N

Mathematical Definition

Visualization

cf9 landscape