Save a scenario for post-processing

from __future__ import annotations

from gemseo import create_design_space
from gemseo import create_discipline
from gemseo import create_scenario

We consider a minimization problem over the interval \([0,1]\) of the \(f(x)=x^2\) objective function:

discipline = create_discipline("AnalyticDiscipline", expressions={"y": "x**2"})

design_space = create_design_space()
design_space.add_variable("x", l_b=0.0, u_b=1.0)

scenario = create_scenario([discipline], "DisciplinaryOpt", "y", design_space)

We solve this optimization problem with the gradient-free algorithm COBYLA:

scenario.execute({"algo": "NLOPT_COBYLA", "max_iter": 10})

Then, we save the results to an HDF5 file for future post-processing:


Total running time of the script: ( 0 minutes 0.000 seconds)

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