discrete_optimization.generic_tools.mutations package

Submodules

discrete_optimization.generic_tools.mutations.mutation_bool module

class discrete_optimization.generic_tools.mutations.mutation_bool.BitFlipMove(attribute: str, list_index_flip: Iterable[int])

Bases: LocalMove

apply_local_move(solution: Solution) → Solution

backtrack_local_move(solution: Solution) → Solution

class discrete_optimization.generic_tools.mutations.mutation_bool.BitFlipMutation(problem: Problem, attribute: str | None = None, probability_flip: float = 0.1, **kwargs: Any)

Bases: SingleAttributeMutation

attribute_type: ListBoolean

attribute_type_cls

alias of ListBoolean

mutate(solution: Solution) → tuple[Solution, LocalMove]

discrete_optimization.generic_tools.mutations.mutation_catalog module

discrete_optimization.generic_tools.mutations.mutation_catalog.get_available_mutations(problem: Problem) → list[tuple[type[SingleAttributeMutation], dict[str, Any], str]]

discrete_optimization.generic_tools.mutations.mutation_integer module

class discrete_optimization.generic_tools.mutations.mutation_integer.IntegerMutation(problem: Problem, attribute: str | None = None, probability_flip: float = 0.1, **kwargs: Any)

Bases: SingleAttributeMutation

attribute_type: ListInteger

attribute_type_cls

alias of ListInteger

mutate(solution: Solution) → tuple[Solution, LocalMove]

discrete_optimization.generic_tools.mutations.mutation_permutation module

class discrete_optimization.generic_tools.mutations.mutation_permutation.PartialShuffleMutation(problem: Problem, attribute: str | None = None, proportion: float = 0.2, **kwargs: Any)

Bases: _BasePermutationMutation

mutate(solution: Solution) → tuple[Solution, LocalMove]

class discrete_optimization.generic_tools.mutations.mutation_permutation.ShuffleMove(attribute: str, new_permutation: list[int] | ndarray, prev_permutation: list[int] | ndarray)

Bases: LocalMove

apply_local_move(solution: Solution) → Solution

backtrack_local_move(solution: Solution) → Solution

class discrete_optimization.generic_tools.mutations.mutation_permutation.ShuffleMutation(problem: Problem, attribute: str | None = None, **kwargs: Any)

Bases: _BasePermutationMutation

mutate(solution: Solution) → tuple[Solution, LocalMove]

class discrete_optimization.generic_tools.mutations.mutation_permutation.SwapMutation(problem: Problem, attribute: str | None = None, nb_swap: int = 1, **kwargs: Any)

Bases: _BasePermutationMutation

mutate(solution: Solution) → tuple[Solution, LocalMove]

class discrete_optimization.generic_tools.mutations.mutation_permutation.SwapsLocalMove(attribute: str, list_index_swap: list[tuple[int, int]])

Bases: LocalMove

apply_local_move(solution: Solution) → Solution

backtrack_local_move(solution: Solution) → Solution

class discrete_optimization.generic_tools.mutations.mutation_permutation.TwoOptMove(attribute: str, index_2opt: list[tuple[int, int]])

Bases: LocalMove

apply_local_move(solution: Solution) → Solution

backtrack_local_move(solution: Solution) → Solution

class discrete_optimization.generic_tools.mutations.mutation_permutation.TwoOptMutation(problem: Problem, attribute: str | None = None, **kwargs: Any)

Bases: _BasePermutationMutation

mutate(solution: Solution) → tuple[Solution, LocalMove]

discrete_optimization.generic_tools.mutations.mutation_portfolio module

class discrete_optimization.generic_tools.mutations.mutation_portfolio.PortfolioMutation(problem: Problem, list_mutations: list[Mutation], weight_mutations: list[float] | ndarray, **kwargs)

Bases: Mutation

Mutations portfolio.

Randomly choose between available mutations.

choose_a_mutation() → int

mutate(solution: Solution) → tuple[Solution, LocalMove]

mutate_and_compute_obj(solution: Solution) → tuple[Solution, LocalMove, dict[str, float]]

discrete_optimization.generic_tools.mutations.mutation_portfolio.create_mutations_portfolio_from_problem(problem: Problem, selected_mutations: Container[type[Mutation]] | None = None, selected_attributes: Container[str] | None = None) → PortfolioMutation

Create a mutation mixing all mutations available in catalog for the solution attributes.

Module contents