BudgetOptimizer

experimental.budget_optimization.optimizer.BudgetOptimizer(
    self,
    objective,
    constraints,
    parametrization_transform=None,
    method='SLSQP',
    tol=None,
    bounds=None,
    options=None,
    callback=None,
)

Budget optimizer using scipy.optimize.minimize.

Parameters

Name	Type	Description	Default
objective	BaseOptimizationObjective	Objective function object	required
constraints	list of BaseConstraint	List of constraint objects	required
decision_variable_transform	BaseDecisionVariableTransform	Decision variable transform object	required
method	str	Optimization method to use. Default is “SLSQP”.	'SLSQP'
tol	float	Tolerance for termination. Default is None.	None
bounds	Union[List[tuple], dict[str, tuple]]	Bounds for decision variables. If a list, the value is used directly in scipy.optimize.minimize. If a dict, the keys are the column names and the values are the bounds for each column. Default is (0, np.inf) for each column.	None
options	dict	Options for the optimization method. Default is None.	None
callback	callable	Callback function to be called after each iteration. Default is None.	None

Methods

Name	Description
wrap_func_with_inv_transform	Wrap a function with parametrization inverse transform

wrap_func_with_inv_transform

experimental.budget_optimization.optimizer.BudgetOptimizer.wrap_func_with_inv_transform(
    fun,
)

Wrap a function with parametrization inverse transform