metaheuristic_designer.operator module#

Base class for the Operator module.

This module implements procedures to modify the current solutions so that we explore the search space.

class Operator(name=None, encoding=None, preserves_order=False, rng=None, **kwargs)[source]#

Bases: ParametrizableMixin, ABC

Abstract base for all perturbation operators.

An Operator modifies a population (typically by applying mutation, crossover, or a composite of several steps). Subclasses must implement evolve().

Parameters:

namestr, optional: Display name for this operator.
encodingEncoding, optional: Post-processing applied to the genotype matrix after the operator runs. Defaults to DefaultEncoding.
preserves_orderbool, optional: If True, the operator keeps individuals in the same order (useful for one-to-one survivor selection). Default False.
rngRNGLike, optional: Random number generator.
**kwargs: Additional keyword arguments stored as schedulable parameters.

Attributes:

params: Access parameter values by attribute-style lookup.

Parameters:

name (Optional[str])
encoding (Optional[Encoding])
preserves_order (bool)
rng (Optional[RNGLike])

Methods

`__call__`(population)	Shorthand for `evolve()`.
`evolve`(population)	Evolves an population using a given strategy.
`gather_params`()	Return the current parameter dictionary (thin wrapper around `get_params()`).
`get_params`()	Return a copy of the current parameter dictionary.
`get_state`()	Gets the current state of the algorithm as a dictionary.
`store_kwargs`([progress])	Store keyword arguments and evaluate them at the given progress.
`update`([progress])	Updates the internal parameters.
`update_kwargs`([progress])	Add or replace parameters and immediately evaluate them.

gather_params()[source]#: Return the current parameter dictionary (thin wrapper around get_params()).

abstract evolve(population)[source]#

Evolves an population using a given strategy.

Return type:

Population

Parameters:

population: Population: The population that will be used.

Returns:

new_population: Population: The modified population.

Parameters:

population (Population)

update(progress=0)[source]#

Updates the internal parameters.

Parameters:: progress (float)

get_state()[source]#

Gets the current state of the algorithm as a dictionary.

Return type:

dict

Returns:

state: dict: The complete state of the operator.

class NullOperator(name=None)[source]#

Bases: Operator

Operator class that returns the individual without changes. Surprisingly useful.

Since it’s a no-op, it has the preserves_order flag set to True.

Parameters:

name: str, optional: Name that is associated with the operator.

Attributes:

params: Access parameter values by attribute-style lookup.

Parameters:

name (Optional[str])

Methods

`__call__`(population)	Shorthand for `evolve()`.
`evolve`(population)	Evolves an population using a given strategy.
`gather_params`()	Return the current parameter dictionary (thin wrapper around `get_params()`).
`get_params`()	Return a copy of the current parameter dictionary.
`get_state`()	Gets the current state of the algorithm as a dictionary.
`store_kwargs`([progress])	Store keyword arguments and evaluate them at the given progress.
`update`([progress])	Updates the internal parameters.
`update_kwargs`([progress])	Add or replace parameters and immediately evaluate them.

evolve(population)[source]#

Evolves an population using a given strategy.

Return type:

Population

Parameters:

population: Population: The population that will be used.

Returns:

new_population: Population: The modified population.

Parameters:

population (Population)

class OperatorFromLambda(operator_fn, name=None, encoding=None, preserves_order=False, rng=None, **kwargs)[source]#

Bases: Operator

Operator that wraps a user‑supplied function.

The function receives a Population, an Initializer, a random state, and any stored keyword arguments, and must return a modified Population.

Parameters:

operator_fncallable: A function (population, initializer, rng, **kwargs) -> Population.
namestr, optional: Display name (defaults to the function’s __name__).
encodingEncoding, optional: See Operator.
preserves_orderbool, optional: See Operator.
rngRNGLike, optional: See Operator.
**kwargs: Keyword arguments forwarded to Operator and also passed to operator_fn on each call.

Attributes:

params: Access parameter values by attribute-style lookup.

Parameters:

operator_fn (Callable)
name (Optional[str])
encoding (Optional[Encoding])
preserves_order (bool)
rng (Optional[RNGLike])

Methods

`__call__`(population)	Shorthand for `evolve()`.
`evolve`(population)	Evolves an population using a given strategy.
`gather_params`()	Return the current parameter dictionary (thin wrapper around `get_params()`).
`get_params`()	Return a copy of the current parameter dictionary.
`get_state`()	Gets the current state of the algorithm as a dictionary.
`store_kwargs`([progress])	Store keyword arguments and evaluate them at the given progress.
`update`([progress])	Updates the internal parameters.
`update_kwargs`([progress])	Add or replace parameters and immediately evaluate them.

evolve(population)[source]#

Evolves an population using a given strategy.

Return type:

Population

Parameters:

population: Population: The population that will be used.

Returns:

new_population: Population: The modified population.

Parameters:

population (Population)