CRS¶

class CRS(max_evals=1000)[소스]¶

기반 클래스: NLoptOptimizer

Controlled Random Search (CRS) with local mutation optimizer.

Controlled Random Search (CRS) with local mutation is part of the family of the CRS optimizers. The CRS optimizers start with a random population of points, and randomly evolve these points by heuristic rules. In the case of CRS with local mutation, the evolution is a randomized version of the NELDER_MEAD local optimizer.

NLopt global optimizer, derivative-free. For further detail, please refer to https://nlopt.readthedocs.io/en/latest/NLopt_Algorithms/#controlled-random-search-crs-with-local-mutation

매개변수: max_evals (int) – Maximum allowed number of function evaluations.
예외 발생: MissingOptionalLibraryError – NLopt library not installed.

Methods

`get_nlopt_optimizer`	Return NLopt optimizer type
`get_support_level`	return support level dictionary
`gradient_num_diff`	We compute the gradient with the numeric differentiation in the parallel way, around the point x_center.
`minimize`	Minimize the scalar function.
`print_options`	Print algorithm-specific options.
`set_max_evals_grouped`	Set max evals grouped
`set_options`	Sets or updates values in the options dictionary.
`wrap_function`	Wrap the function to implicitly inject the args at the call of the function.

Attributes

bounds_support_level¶: Returns bounds support level

gradient_support_level¶: Returns gradient support level

initial_point_support_level¶: Returns initial point support level

is_bounds_ignored¶: Returns is bounds ignored

is_bounds_required¶: Returns is bounds required

is_bounds_supported¶: Returns is bounds supported

is_gradient_ignored¶: Returns is gradient ignored

is_gradient_required¶: Returns is gradient required

is_gradient_supported¶: Returns is gradient supported

is_initial_point_ignored¶: Returns is initial point ignored

is_initial_point_required¶: Returns is initial point required

is_initial_point_supported¶: Returns is initial point supported

setting¶: Return setting

settings¶