HyperHeuristic

Module: opytimizer.core.hyperheuristic

A HyperHeuristic class that manages multiple low-level optimizers and provides high-level strategies for algorithm selection and adaptation.

It supports both single-objective and multi-objective optimization by allowing a custom performance_metric function to be passed (e.g., min_fitness, hypervolume, etc).

It also supports parameter adaptation and strategy adaptation mechanisms.

Constructor

HyperHeuristic(optimizers: Optional[List[opytimizer.core.optimizer.Optimizer]] = None, performance_metric: Optional[Callable[[Any], float]] = None) -> None

Parameters

Parameter	Type	Default	Description
optimizers	Optional[List[opytimizer.core.optimizer.Optimizer]]	None	—
performance_metric	Optional[Callable[[Any], float]]	None	—

Methods

add_optimizer

add_optimizer(self, optimizer: opytimizer.core.optimizer.Optimizer) -> None

Parameters

Parameter	Type	Default	Description
optimizer	opytimizer.core.optimizer.Optimizer		—

compile

compile(self, space: Union[opytimizer.core.space._SingleObjectiveSpace, opytimizer.core.space._MultiObjectiveSpace]) -> None

Compiles additional information that is used by this optimizer.

This method is called before the optimization procedure and makes sure that the additional variable is available as a property.

Parameters

Parameter	Type	Default	Description
space	Union[opytimizer.core.space._SingleObjectiveSpace, opytimizer.core.space._MultiObjectiveSpace]		—

evaluate

evaluate(self, space: Union[opytimizer.core.space._SingleObjectiveSpace, opytimizer.core.space._MultiObjectiveSpace], function: opytimizer.core.function.Function) -> None

Evaluates the search space according to the objective function.

If you need a specific evaluate method, please re-implement it on child's class.

Also, note that function only accept arguments that are found on Opytimizer class.

Parameters

Parameter	Type	Default	Description
space	Union[opytimizer.core.space._SingleObjectiveSpace, opytimizer.core.space._MultiObjectiveSpace]		A Space object that will be evaluated.
function	opytimizer.core.function.Function		A Function object serving as an objective function.

get_average_performance

get_average_performance(self, optimizer_name: str) -> Optional[float]

Parameters

Parameter	Type	Default	Description
optimizer_name	str		—

get_best_performance

get_best_performance(self, optimizer_name: str) -> Optional[float]

Parameters

Parameter	Type	Default	Description
optimizer_name	str		—

get_statistics

get_statistics(self) -> Dict[str, Any]

remove_optimizer

remove_optimizer(self, optimizer_name: str) -> None

Parameters

Parameter	Type	Default	Description
optimizer_name	str		—

select_optimizer

select_optimizer(self, space: Union[opytimizer.core.space._SingleObjectiveSpace, opytimizer.core.space._MultiObjectiveSpace], function: opytimizer.core.function.Function) -> opytimizer.core.optimizer.Optimizer

Parameters

Parameter	Type	Default	Description
space	Union[opytimizer.core.space._SingleObjectiveSpace, opytimizer.core.space._MultiObjectiveSpace]		—
function	opytimizer.core.function.Function		—

update

update(self, space: Union[opytimizer.core.space._SingleObjectiveSpace, opytimizer.core.space._MultiObjectiveSpace], function: opytimizer.core.function.Function = None) -> None

Updates the agents' position array.

As each child has a different procedure of update, you will need to implement it directly on its class.

Parameters

Parameter	Type	Default	Description
space	Union[opytimizer.core.space._SingleObjectiveSpace, opytimizer.core.space._MultiObjectiveSpace]		—
function	opytimizer.core.function.Function	None	—

update_performance

update_performance(self, optimizer: opytimizer.core.optimizer.Optimizer, space: Union[opytimizer.core.space._SingleObjectiveSpace, opytimizer.core.space._MultiObjectiveSpace]) -> None

Parameters

Parameter	Type	Default	Description
optimizer	opytimizer.core.optimizer.Optimizer		—
space	Union[opytimizer.core.space._SingleObjectiveSpace, opytimizer.core.space._MultiObjectiveSpace]		—