gemseo.formulations.bilevel module#

A Bi-level formulation.

class BiLevel(disciplines, objective_name, design_space, settings_model=None, **settings)[source]#

Bases: BaseMDOFormulation

A bi-level formulation.

This formulation draws an optimization architecture that involves multiple optimization problems to be solved to obtain the solution of the MDO problem.

Here, at each iteration on the global design variables, the bi-level MDO formulation implementation performs:

  1. a first MDA to compute the coupling variables,

  2. several disciplinary optimizations on the local design variables in parallel,

  3. a second MDA to update the coupling variables.

Initialize self. See help(type(self)) for accurate signature.

Parameters:

  • disciplines (Sequence[Discipline]) -- The disciplines.

  • objective_name (str) -- The name(s) of the discipline output(s) used as objective. If multiple names are passed, the objective will be a vector.

  • design_space (DesignSpace) -- The design space.

  • settings_model (BiLevel_Settings | None) -- The settings of the formulation as a Pydantic model. If None, use **settings.

  • **settings (Any) -- The settings of the formulation. This argument is ignored when settings_model is not None.

Settings#

alias of BiLevel_Settings

add_constraint(output_name, constraint_type=ConstraintType.EQ, constraint_name='', value=0, positive=False, levels=())[source]#

Add a constraint to the formulation.

Parameters:

  • output_name (str) -- The name(s) of the outputs computed by \(c(x)\). If several names are given, a single discipline must provide all outputs.

  • constraint_type (ConstraintType) --

    The type of constraint.

    By default it is set to "eq".

  • constraint_name (str) --

    The name of the constraint to be stored. If empty, the name of the constraint is generated from output_name, constraint_type, value and positive.

    By default it is set to "".

  • value (float) --

    The value \(a\).

    By default it is set to 0.

  • positive (bool) --

    Whether the inequality constraint is positive.

    By default it is set to False.

  • levels (list[str]) --

    The levels at which the constraint is to be added (sublist of LEVELS). By default, the policy set at the initialization of the formulation is enforced.

    By default it is set to ().

Raises:

ValueError -- When the constraint levels are not a sublist of BiLevel.LEVELS.

Return type:

None

classmethod get_default_sub_option_values(**options)[source]#
Raises:

ValueError -- When the MDA name is not provided.

Parameters:

options (str)

Return type:

StrKeyMapping

classmethod get_sub_options_grammar(**options)[source]#

Return the grammar of the selected MDA.

Parameters:

**options (str) -- The options of the BiLevel formulation.

Returns:

The MDA grammar.

Raises:

ValueError -- When the MDA name is not provided.

Return type:

JSONGrammar

get_top_level_disciplines()[source]#

Return the disciplines which inputs are required to run the scenario.

A formulation seeks to compute the objective and constraints from the input variables. It structures the optimization problem into multiple levels of disciplines. The disciplines directly depending on these inputs are called top level disciplines.

By default, this method returns all disciplines. This method can be overloaded by subclasses.

Returns:

The top level disciplines.

Return type:

tuple[Discipline]

DEFAULT_SCENARIO_RESULT_CLASS_NAME: ClassVar[str] = 'BiLevelScenarioResult'#

The name of the ScenarioResult class to be used for post-processing.

LEVELS = ('system', 'sub-scenarios')#
SUBSCENARIOS_LEVEL = 'sub-scenarios'#
SYSTEM_LEVEL = 'system'#
property mda1: BaseMDA | None#

The MDA1 instance.

property mda2: BaseMDA#

The MDA2 instance.