saealib.GA¶

class saealib.GA(crossover, mutation, parent_selection, survivor_selection, repair=<function repair_clipping>)[source]¶

Genetic Algorithm class.

Parameters:

crossover¶

Crossover operator.

mutation¶

Mutation operator.

parent_selection¶

Parent selection operator.

survivor_selection¶

Survivor selection operator.

Methods

`__init__`	Initialize GA (Genetic Algorithm) class.
`ask`	Generate offspring via crossover and mutation.
`get_required_attrs`	Return algorithm-specific attributes (GA needs none beyond the defaults).
`tell`	Update the population using (μ+λ) survivor selection.

Method Details

GA.__init__(crossover, mutation, parent_selection, survivor_selection, repair=<function repair_clipping>)[source]¶

Initialize GA (Genetic Algorithm) class.

Parameters:

crossover (Crossover) – Crossover operator.
mutation (Mutation) – Mutation operator.
parent_selection (ParentSelection) – Parent selection operator.
survivor_selection (SurvivorSelection) – Survivor selection operator.
repair (RepairFunc or None, optional) – Repair function applied after crossover and after mutation. Defaults to repair_clipping. Pass None to disable repair.

GA.ask(ctx, provider, n_offspring=None)[source]¶

Generate offspring via crossover and mutation.

Parameters:

ctx (OptimizationContext) – Current optimization context.
provider (ComponentProvider) – Component provider.
n_offspring (int or None, optional) – Number of offspring. Defaults to the current population size.

Return type:

Population

GA.get_required_attrs(problem)[source]¶

Return algorithm-specific attributes (GA needs none beyond the defaults).

GA.tell(ctx, provider, offspring)[source]¶

Update the population using (μ+λ) survivor selection.

Parameters: