gemseo / formulations

# disciplinary_opt module¶

## A formulation for uncoupled or weakly coupled problems¶

class gemseo.formulations.disciplinary_opt.DisciplinaryOpt(disciplines, objective_name, design_space, maximize_objective=False)[source]

The disciplinary optimization formulation draws the architecture of a mono disciplinary optimization process from an ordered list of disciplines, an objective function and a design space. The objective function is minimized by default.

Constructor, initializes the objective functions and constraints

Parameters
• disciplines (list(MDODiscipline)) – the disciplines list.

• objective_name (str) – the objective function data name.

• design_space (DesignSpace) – the design space.

• maximize_objective (bool) – if True, the objective function is maximized, by default, a minimization is performed.

get_expected_dataflow()[source]

Returns the expected data exchange sequence, used for xdsm representation

get_expected_workflow()[source]

Returns the expected execution sequence, used for xdsm representation

get_top_level_disc()[source]

Returns the disciplines which inputs are required to run the associated scenario By default, returns all disciplines To be overloaded by subclasses

Returns

the list of top level disciplines