gemseo.disciplines.ode package#
Scenario adapters.
A scenario adapter is an MDODiscipline wrapping a Scenario.
A call to MDODiscipline.execute() triggers calls to Scenario.execute().
For instance, let us consider an MDOScenario defining a gradient-based
constrained minimization of a cost function over a DesignSpace from several
MDODiscipline instances. If this optimization problem is not convex, it is
advisable to set up a multi-start strategy to repeat this minimization from different
starting points. in order to find a good local minimum. In this case, an
MDOScenarioAdapter takes a design value as input, use it as initial design
value of the minimization algorithm and outputs some variables of interest such as the
objective and constraints at the optimum. Then, this MDOScenarioAdapter can be
used as any MDODiscipline in a DOEScenario defining a sampling-based
version of the previous problem. In other words, this DOEScenario repeats the
gradient-based optimization from several starting points and returns the best local
minimum.
The scenario adapters can also be useful for bi-level optimization. Let us consider an
optimization problem with two design variables, namely \(x_1\) and \(x_2\). The
wrapped MDOScenario solves the optimization problem with respect to the design
variables \(x_1\) and another MDOScenario considers this
MDOScenarioAdapter to solve the optimization problem with respect to
\(x_2\). It is particularly relevant when the design variables have different
natures, e.g. \(x_1\) is discrete and \(x_2\) is continuous, and that dedicated
algorithms exist.