poli.objective_repository.toy_continuous_problem.toy_continuous_problem.ToyContinuousProblem

class poli.objective_repository.toy_continuous_problem.toy_continuous_problem.ToyContinuousProblem(name: Literal['ackley_function_01', 'alpine_01', 'alpine_02', 'bent_cigar', 'brown', 'chung_reynolds', 'cosine_mixture', 'deb_01', 'deb_02', 'deflected_corrugated_spring', 'styblinski_tang', 'shifted_sphere', 'easom', 'cross_in_tray', 'egg_holder', 'camelback_2d', 'branin_2d', 'hartmann_6d', 'rosenbrock', 'levy'], n_dims: int = 2, embed_in: Optional[int] = None, dimensions_to_embed_in: Optional[List[int]] = None)

Contains the toy objective functions, their limits, and the optima location.

For more information, check definitions.py and [1].

[1]: https://al-roomi.org/benchmarks/unconstrained/n-dimensions

__init__(name: Literal['ackley_function_01', 'alpine_01', 'alpine_02', 'bent_cigar', 'brown', 'chung_reynolds', 'cosine_mixture', 'deb_01', 'deb_02', 'deflected_corrugated_spring', 'styblinski_tang', 'shifted_sphere', 'easom', 'cross_in_tray', 'egg_holder', 'camelback_2d', 'branin_2d', 'hartmann_6d', 'rosenbrock', 'levy'], n_dims: int = 2, embed_in: Optional[int] = None, dimensions_to_embed_in: Optional[List[int]] = None) → None

Methods

__init__(name[, n_dims, embed_in, ...])
evaluate_objective(x, **kwargs)