ESCH

class ESCH(max_evals=1000)

ESCH evolutionary optimizer.

ESCH is an evolutionary algorithm for global optimization that supports bound constraints only. Specifically, it does not support nonlinear constraints.

NLopt global optimizer, derivative-free. For further detail, please refer to

http://nlopt.readthedocs.io/en/latest/NLopt_Algorithms/#esch-evolutionary-algorithm

Parameters

max_evals (int) – Maximum allowed number of function evaluations.

Raises

NameError – NLopt library not installed.

Attributes

ESCH.bounds_support_level	Returns bounds support level
ESCH.gradient_support_level	Returns gradient support level
ESCH.initial_point_support_level	Returns initial point support level
ESCH.is_bounds_ignored	Returns is bounds ignored
ESCH.is_bounds_required	Returns is bounds required
ESCH.is_bounds_supported	Returns is bounds supported
ESCH.is_gradient_ignored	Returns is gradient ignored
ESCH.is_gradient_required	Returns is gradient required
ESCH.is_gradient_supported	Returns is gradient supported
ESCH.is_initial_point_ignored	Returns is initial point ignored
ESCH.is_initial_point_required	Returns is initial point required
ESCH.is_initial_point_supported	Returns is initial point supported
ESCH.setting	Return setting

Methods

ESCH.get_nlopt_optimizer()	Return NLopt optimizer type
ESCH.get_support_level()	return support level dictionary
ESCH.gradient_num_diff(x_center, f, epsilon)	We compute the gradient with the numeric differentiation in the parallel way, around the point x_center.
ESCH.optimize(num_vars, objective_function)	Perform optimization.
ESCH.print_options()	Print algorithm-specific options.
ESCH.set_max_evals_grouped(limit)	Set max evals grouped
ESCH.set_options(**kwargs)	Sets or updates values in the options dictionary.
ESCH.wrap_function(function, args)	Wrap the function to implicitly inject the args at the call of the function.