simulated_annealing module

Define the simulated annealing algorithm.

class SimulatedAnnealing(*, compensating_elements, elts, objectives, variables, compute_beam_propagation, compute_residuals, cavity_settings_factory, reference_simulation_output, constraints=None, compute_constraints=None, optimisation_algorithm_kwargs=None, history_kwargs=None, **kwargs)[source]

Bases: OptimisationAlgorithm

Simulated Annealing method for global optimization.

Parameters:

compensating_elements (Collection[Element])
elts (ListOfElements)
objectives (Collection[Objective])
variables (Collection[Variable])
compute_beam_propagation (Callable[[SetOfCavitySettings], SimulationOutput])
compute_residuals (Callable[[SimulationOutput], Any])
cavity_settings_factory (CavitySettingsFactory)
reference_simulation_output (SimulationOutput)
constraints (Collection[Constraint] | None, default: None)
compute_constraints (Callable[[SimulationOutput], ndarray] | None, default: None)
optimisation_algorithm_kwargs (dict[str, Any] | None, default: None)
history_kwargs (dict[str, Any] | None, default: None)

supports_constraints: bool = False

optimize()[source]

Set up and run the simulated annealing algorithm.

Return type:: OptiSol
Returns:: Contains solution(s), objective value(s), status, etc.

property _default_kwargs: dict[str, Any]: Default parameters for dual_annealing.

_generate_opti_sol(result)[source]

Package the results into an OptiSol dictionary.

Parameters:: result (OptimizeResult)
Return type:: OptiSol

_format_bounds()[source]

Convert Variable objects to a list of bounds.

Return type:: list[tuple[float, float]]

_abc_impl = <_abc._abc_data object at 0x75e516dc7d80>