.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples/scenario_adapter/plot_multistart_example.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_examples_scenario_adapter_plot_multistart_example.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_examples_scenario_adapter_plot_multistart_example.py:


Multistart optimization
=======================

Runs simple optimization problem with multiple starting points
Nests an :class:`.MDOScenario` in a :class:`.DOEScenario`
using an :class:`.MDOScenarioAdapter`.

.. GENERATED FROM PYTHON SOURCE LINES 29-41

.. code-block:: Python


    from __future__ import annotations

    from gemseo import configure_logger
    from gemseo import create_design_space
    from gemseo import create_discipline
    from gemseo import create_scenario
    from gemseo.disciplines.scenario_adapters.mdo_scenario_adapter import MDOScenarioAdapter

    configure_logger()






.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    <RootLogger root (INFO)>



.. GENERATED FROM PYTHON SOURCE LINES 42-44

Create the disciplines
----------------------

.. GENERATED FROM PYTHON SOURCE LINES 44-49

.. code-block:: Python

    objective = create_discipline("AnalyticDiscipline", expressions={"obj": "x**3-x+1"})
    constraint = create_discipline(
        "AnalyticDiscipline", expressions={"cstr": "x**2+obj**2-1.5"}
    )








.. GENERATED FROM PYTHON SOURCE LINES 50-52

Create the design space
-----------------------

.. GENERATED FROM PYTHON SOURCE LINES 52-55

.. code-block:: Python

    design_space = create_design_space()
    design_space.add_variable("x", l_b=-1.5, u_b=1.5, value=1.5)








.. GENERATED FROM PYTHON SOURCE LINES 56-58

Create the MDO scenario
-----------------------

.. GENERATED FROM PYTHON SOURCE LINES 58-67

.. code-block:: Python

    scenario = create_scenario(
        [objective, constraint],
        "DisciplinaryOpt",
        "obj",
        design_space,
    )
    scenario.default_inputs = {"algo": "SLSQP", "max_iter": 10}
    scenario.add_constraint("cstr", constraint_type="ineq")








.. GENERATED FROM PYTHON SOURCE LINES 68-70

Create the scenario adapter
---------------------------

.. GENERATED FROM PYTHON SOURCE LINES 70-75

.. code-block:: Python

    dv_names = scenario.formulation.opt_problem.design_space.variable_names
    adapter = MDOScenarioAdapter(
        scenario, dv_names, ["obj", "cstr"], set_x0_before_opt=True
    )








.. GENERATED FROM PYTHON SOURCE LINES 76-78

Create the DOE scenario
-----------------------

.. GENERATED FROM PYTHON SOURCE LINES 78-89

.. code-block:: Python

    scenario_doe = create_scenario(
        adapter,
        "DisciplinaryOpt",
        "obj",
        design_space,
        scenario_type="DOE",
    )
    scenario_doe.add_constraint("cstr", constraint_type="ineq")
    run_inputs = {"n_samples": 10, "algo": "fullfact"}
    scenario_doe.execute(run_inputs)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

        INFO - 13:08:48:  
        INFO - 13:08:48: *** Start DOEScenario execution ***
        INFO - 13:08:48: DOEScenario
        INFO - 13:08:48:    Disciplines: MDOScenario_adapter
        INFO - 13:08:48:    MDO formulation: DisciplinaryOpt
        INFO - 13:08:48: Optimization problem:
        INFO - 13:08:48:    minimize obj(x)
        INFO - 13:08:48:    with respect to x
        INFO - 13:08:48:    subject to constraints:
        INFO - 13:08:48:       cstr(x) <= 0.0
        INFO - 13:08:48:    over the design space:
        INFO - 13:08:48:       +------+-------------+-------+-------------+-------+
        INFO - 13:08:48:       | Name | Lower bound | Value | Upper bound | Type  |
        INFO - 13:08:48:       +------+-------------+-------+-------------+-------+
        INFO - 13:08:48:       | x    |     -1.5    |  1.5  |     1.5     | float |
        INFO - 13:08:48:       +------+-------------+-------+-------------+-------+
        INFO - 13:08:48: Solving optimization problem with algorithm fullfact:
        INFO - 13:08:48:  
        INFO - 13:08:48: *** Start MDOScenario execution ***
        INFO - 13:08:48: MDOScenario
        INFO - 13:08:48:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 13:08:48:    MDO formulation: DisciplinaryOpt
        INFO - 13:08:48: Optimization problem:
        INFO - 13:08:48:    minimize obj(x)
        INFO - 13:08:48:    with respect to x
        INFO - 13:08:48:    subject to constraints:
        INFO - 13:08:48:       cstr(x) <= 0.0
        INFO - 13:08:48:    over the design space:
        INFO - 13:08:48:       +------+-------------+-------+-------------+-------+
        INFO - 13:08:48:       | Name | Lower bound | Value | Upper bound | Type  |
        INFO - 13:08:48:       +------+-------------+-------+-------------+-------+
        INFO - 13:08:48:       | x    |     -1.5    |  -1.5 |     1.5     | float |
        INFO - 13:08:48:       +------+-------------+-------+-------------+-------+
        INFO - 13:08:48: Solving optimization problem with algorithm SLSQP:
        INFO - 13:08:48:     10%|█         | 1/10 [00:00<00:00, 134.07 it/sec, obj=-0.875]
        INFO - 13:08:48:     20%|██        | 2/10 [00:00<00:00, 162.93 it/sec, obj=-0.267]
        INFO - 13:08:48:     30%|███       | 3/10 [00:00<00:00, 215.86 it/sec, obj=-0.809]
        INFO - 13:08:48:     40%|████      | 4/10 [00:00<00:00, 255.66 it/sec, obj=-0.868]
        INFO - 13:08:48:     50%|█████     | 5/10 [00:00<00:00, 288.92 it/sec, obj=-0.872]
        INFO - 13:08:48:     60%|██████    | 6/10 [00:00<00:00, 298.66 it/sec, obj=-0.265]
        INFO - 13:08:48:     70%|███████   | 7/10 [00:00<00:00, 306.95 it/sec, obj=0.136]
        INFO - 13:08:48:     80%|████████  | 8/10 [00:00<00:00, 313.68 it/sec, obj=0.579]
        INFO - 13:08:48:     90%|█████████ | 9/10 [00:00<00:00, 330.96 it/sec, obj=0.289]
        INFO - 13:08:48:    100%|██████████| 10/10 [00:00<00:00, 333.99 it/sec, obj=1.25]
     WARNING - 13:08:48: Optimization found no feasible point !  The least infeasible point is selected.
        INFO - 13:08:48: Optimization result:
        INFO - 13:08:48:    Optimizer info:
        INFO - 13:08:48:       Status: None
        INFO - 13:08:48:       Message: Maximum number of iterations reached. GEMSEO Stopped the driver
        INFO - 13:08:48:       Number of calls to the objective function by the optimizer: 12
        INFO - 13:08:48:    Solution:
     WARNING - 13:08:48:       The solution is not feasible.
        INFO - 13:08:48:       Objective: 0.2888129873625884
        INFO - 13:08:48:       Standardized constraints:
        INFO - 13:08:48:          cstr = 0.1513713660745195
        INFO - 13:08:48:       Design space:
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | x    |     -1.5    | -1.252181466244097 |     1.5     | float |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48: *** End MDOScenario execution (time: 0:00:00.046121) ***
        INFO - 13:08:48:     10%|█         | 1/10 [00:00<00:00, 18.97 it/sec, obj=0.289]
        INFO - 13:08:48:  
        INFO - 13:08:48: *** Start MDOScenario execution ***
        INFO - 13:08:48: MDOScenario
        INFO - 13:08:48:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 13:08:48:    MDO formulation: DisciplinaryOpt
        INFO - 13:08:48: Optimization problem:
        INFO - 13:08:48:    minimize obj(x)
        INFO - 13:08:48:    with respect to x
        INFO - 13:08:48:    subject to constraints:
        INFO - 13:08:48:       cstr(x) <= 0.0
        INFO - 13:08:48:    over the design space:
        INFO - 13:08:48:       +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:       | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 13:08:48:       +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:       | x    |     -1.5    | -1.166666666666667 |     1.5     | float |
        INFO - 13:08:48:       +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48: Solving optimization problem with algorithm SLSQP:
        INFO - 13:08:48:     10%|█         | 1/10 [00:00<00:00, 754.78 it/sec, obj=0.579]
        INFO - 13:08:48:     20%|██        | 2/10 [00:00<00:00, 381.68 it/sec, obj=-0.875]
        INFO - 13:08:48:     30%|███       | 3/10 [00:00<00:00, 372.34 it/sec, obj=-0.267]
        INFO - 13:08:48:     40%|████      | 4/10 [00:00<00:00, 406.53 it/sec, obj=-0.809]
        INFO - 13:08:48:     50%|█████     | 5/10 [00:00<00:00, 432.25 it/sec, obj=-0.868]
        INFO - 13:08:48:     60%|██████    | 6/10 [00:00<00:00, 453.51 it/sec, obj=-0.874]
        INFO - 13:08:48:     70%|███████   | 7/10 [00:00<00:00, 437.87 it/sec, obj=-0.266]
        INFO - 13:08:48:     80%|████████  | 8/10 [00:00<00:00, 428.02 it/sec, obj=0.135]
        INFO - 13:08:48:     90%|█████████ | 9/10 [00:00<00:00, 419.65 it/sec, obj=0.577]
        INFO - 13:08:48:    100%|██████████| 10/10 [00:00<00:00, 432.24 it/sec, obj=0.288]
     WARNING - 13:08:48: Optimization found no feasible point !  The least infeasible point is selected.
        INFO - 13:08:48: Optimization result:
        INFO - 13:08:48:    Optimizer info:
        INFO - 13:08:48:       Status: None
        INFO - 13:08:48:       Message: Maximum number of iterations reached. GEMSEO Stopped the driver
        INFO - 13:08:48:       Number of calls to the objective function by the optimizer: 12
        INFO - 13:08:48:    Solution:
     WARNING - 13:08:48:       The solution is not feasible.
        INFO - 13:08:48:       Objective: 0.28811314244670916
        INFO - 13:08:48:       Standardized constraints:
        INFO - 13:08:48:          cstr = 0.15144075010172386
        INFO - 13:08:48:       Design space:
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | x    |     -1.5    | -1.252370379421043 |     1.5     | float |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48: *** End MDOScenario execution (time: 0:00:00.037626) ***
        INFO - 13:08:48:     20%|██        | 2/10 [00:00<00:00, 21.77 it/sec, obj=0.288]
        INFO - 13:08:48:  
        INFO - 13:08:48: *** Start MDOScenario execution ***
        INFO - 13:08:48: MDOScenario
        INFO - 13:08:48:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 13:08:48:    MDO formulation: DisciplinaryOpt
        INFO - 13:08:48: Optimization problem:
        INFO - 13:08:48:    minimize obj(x)
        INFO - 13:08:48:    with respect to x
        INFO - 13:08:48:    subject to constraints:
        INFO - 13:08:48:       cstr(x) <= 0.0
        INFO - 13:08:48:    over the design space:
        INFO - 13:08:48:       +------+-------------+---------------------+-------------+-------+
        INFO - 13:08:48:       | Name | Lower bound |        Value        | Upper bound | Type  |
        INFO - 13:08:48:       +------+-------------+---------------------+-------------+-------+
        INFO - 13:08:48:       | x    |     -1.5    | -0.8333333333333334 |     1.5     | float |
        INFO - 13:08:48:       +------+-------------+---------------------+-------------+-------+
        INFO - 13:08:48: Solving optimization problem with algorithm SLSQP:
        INFO - 13:08:48:     10%|█         | 1/10 [00:00<00:00, 724.66 it/sec, obj=1.25]
        INFO - 13:08:48:     20%|██        | 2/10 [00:00<00:00, 373.52 it/sec, obj=-0.875]
        INFO - 13:08:48:     30%|███       | 3/10 [00:00<00:00, 427.39 it/sec, obj=1.01]
        INFO - 13:08:48:     40%|████      | 4/10 [00:00<00:00, 402.37 it/sec, obj=-0.875]
        INFO - 13:08:48:     50%|█████     | 5/10 [00:00<00:00, 427.91 it/sec, obj=0.819]
        INFO - 13:08:48:     60%|██████    | 6/10 [00:00<00:00, 404.93 it/sec, obj=-0.875]
        INFO - 13:08:48:     70%|███████   | 7/10 [00:00<00:00, 421.39 it/sec, obj=0.693]
        INFO - 13:08:48:     80%|████████  | 8/10 [00:00<00:00, 411.40 it/sec, obj=-0.875]
        INFO - 13:08:48:     90%|█████████ | 9/10 [00:00<00:00, 423.71 it/sec, obj=0.584]
        INFO - 13:08:48:    100%|██████████| 10/10 [00:00<00:00, 416.32 it/sec, obj=-0.875]
     WARNING - 13:08:48: Optimization found no feasible point !  The least infeasible point is selected.
        INFO - 13:08:48: Optimization result:
        INFO - 13:08:48:    Optimizer info:
        INFO - 13:08:48:       Status: None
        INFO - 13:08:48:       Message: Maximum number of iterations reached. GEMSEO Stopped the driver
        INFO - 13:08:48:       Number of calls to the objective function by the optimizer: 12
        INFO - 13:08:48:    Solution:
     WARNING - 13:08:48:       The solution is not feasible.
        INFO - 13:08:48:       Objective: 0.5837798748832244
        INFO - 13:08:48:       Standardized constraints:
        INFO - 13:08:48:          cstr = 0.19806414473664136
        INFO - 13:08:48:       Design space:
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | x    |     -1.5    | -1.165017254128868 |     1.5     | float |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48: *** End MDOScenario execution (time: 0:00:00.037045) ***
        INFO - 13:08:48:     30%|███       | 3/10 [00:00<00:00, 22.87 it/sec, obj=0.584]
        INFO - 13:08:48:  
        INFO - 13:08:48: *** Start MDOScenario execution ***
        INFO - 13:08:48: MDOScenario
        INFO - 13:08:48:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 13:08:48:    MDO formulation: DisciplinaryOpt
        INFO - 13:08:48: Optimization problem:
        INFO - 13:08:48:    minimize obj(x)
        INFO - 13:08:48:    with respect to x
        INFO - 13:08:48:    subject to constraints:
        INFO - 13:08:48:       cstr(x) <= 0.0
        INFO - 13:08:48:    over the design space:
        INFO - 13:08:48:       +------+-------------+-------+-------------+-------+
        INFO - 13:08:48:       | Name | Lower bound | Value | Upper bound | Type  |
        INFO - 13:08:48:       +------+-------------+-------+-------------+-------+
        INFO - 13:08:48:       | x    |     -1.5    |  -0.5 |     1.5     | float |
        INFO - 13:08:48:       +------+-------------+-------+-------------+-------+
        INFO - 13:08:48: Solving optimization problem with algorithm SLSQP:
        INFO - 13:08:48:     10%|█         | 1/10 [00:00<00:00, 734.30 it/sec, obj=1.38]
        INFO - 13:08:48:     20%|██        | 2/10 [00:00<00:00, 355.87 it/sec, obj=2.88]
        INFO - 13:08:48:     30%|███       | 3/10 [00:00<00:00, 414.31 it/sec, obj=1.23]
        INFO - 13:08:48:     40%|████      | 4/10 [00:00<00:00, 398.43 it/sec, obj=2.87]
        INFO - 13:08:48:     50%|█████     | 5/10 [00:00<00:00, 426.48 it/sec, obj=0.848]
        INFO - 13:08:48:     60%|██████    | 6/10 [00:00<00:00, 398.77 it/sec, obj=0.658]
        INFO - 13:08:48:     70%|███████   | 7/10 [00:00<00:00, 383.22 it/sec, obj=0.643]
        INFO - 13:08:48:     80%|████████  | 8/10 [00:00<00:00, 373.78 it/sec, obj=0.616]
        INFO - 13:08:48:     90%|█████████ | 9/10 [00:00<00:00, 367.63 it/sec, obj=0.615]
        INFO - 13:08:48:    100%|██████████| 10/10 [00:00<00:00, 357.28 it/sec, obj=0.615]
        INFO - 13:08:48: Optimization result:
        INFO - 13:08:48:    Optimizer info:
        INFO - 13:08:48:       Status: None
        INFO - 13:08:48:       Message: Maximum number of iterations reached. GEMSEO Stopped the driver
        INFO - 13:08:48:       Number of calls to the objective function by the optimizer: 13
        INFO - 13:08:48:    Solution:
        INFO - 13:08:48:       The solution is feasible.
        INFO - 13:08:48:       Objective: 0.6150998219543254
        INFO - 13:08:48:       Standardized constraints:
        INFO - 13:08:48:          cstr = -0.788285881879476
        INFO - 13:08:48:       Design space:
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | x    |     -1.5    | 0.5773788419679762 |     1.5     | float |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48: *** End MDOScenario execution (time: 0:00:00.042287) ***
        INFO - 13:08:48:     40%|████      | 4/10 [00:00<00:00, 22.88 it/sec, obj=0.615]
        INFO - 13:08:48:  
        INFO - 13:08:48: *** Start MDOScenario execution ***
        INFO - 13:08:48: MDOScenario
        INFO - 13:08:48:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 13:08:48:    MDO formulation: DisciplinaryOpt
        INFO - 13:08:48: Optimization problem:
        INFO - 13:08:48:    minimize obj(x)
        INFO - 13:08:48:    with respect to x
        INFO - 13:08:48:    subject to constraints:
        INFO - 13:08:48:       cstr(x) <= 0.0
        INFO - 13:08:48:    over the design space:
        INFO - 13:08:48:       +------+-------------+---------------------+-------------+-------+
        INFO - 13:08:48:       | Name | Lower bound |        Value        | Upper bound | Type  |
        INFO - 13:08:48:       +------+-------------+---------------------+-------------+-------+
        INFO - 13:08:48:       | x    |     -1.5    | -0.1666666666666667 |     1.5     | float |
        INFO - 13:08:48:       +------+-------------+---------------------+-------------+-------+
        INFO - 13:08:48: Solving optimization problem with algorithm SLSQP:
        INFO - 13:08:48:     10%|█         | 1/10 [00:00<00:00, 729.44 it/sec, obj=1.16]
        INFO - 13:08:48:     20%|██        | 2/10 [00:00<00:00, 376.15 it/sec, obj=2.87]
        INFO - 13:08:48:     30%|███       | 3/10 [00:00<00:00, 427.19 it/sec, obj=0.785]
        INFO - 13:08:48:     40%|████      | 4/10 [00:00<00:00, 389.41 it/sec, obj=2.88]
        INFO - 13:08:48:     50%|█████     | 5/10 [00:00<00:00, 402.82 it/sec, obj=0.644]
        INFO - 13:08:48:     60%|██████    | 6/10 [00:00<00:00, 384.70 it/sec, obj=0.624]
        INFO - 13:08:48:     70%|███████   | 7/10 [00:00<00:00, 372.30 it/sec, obj=0.615]
        INFO - 13:08:48:     80%|████████  | 8/10 [00:00<00:00, 364.91 it/sec, obj=0.615]
        INFO - 13:08:48:     90%|█████████ | 9/10 [00:00<00:00, 358.08 it/sec, obj=0.615]
        INFO - 13:08:48:    100%|██████████| 10/10 [00:00<00:00, 353.85 it/sec, obj=0.615]
        INFO - 13:08:48: Optimization result:
        INFO - 13:08:48:    Optimizer info:
        INFO - 13:08:48:       Status: None
        INFO - 13:08:48:       Message: Maximum number of iterations reached. GEMSEO Stopped the driver
        INFO - 13:08:48:       Number of calls to the objective function by the optimizer: 12
        INFO - 13:08:48:    Solution:
        INFO - 13:08:48:       The solution is feasible.
        INFO - 13:08:48:       Objective: 0.6150998205402495
        INFO - 13:08:48:       Standardized constraints:
        INFO - 13:08:48:          cstr = -0.7883188793606977
        INFO - 13:08:48:       Design space:
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | x    |     -1.5    | 0.5773502675245377 |     1.5     | float |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48: *** End MDOScenario execution (time: 0:00:00.042874) ***
        INFO - 13:08:48:     50%|█████     | 5/10 [00:00<00:00, 22.80 it/sec, obj=0.615]
        INFO - 13:08:48:  
        INFO - 13:08:48: *** Start MDOScenario execution ***
        INFO - 13:08:48: MDOScenario
        INFO - 13:08:48:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 13:08:48:    MDO formulation: DisciplinaryOpt
        INFO - 13:08:48: Optimization problem:
        INFO - 13:08:48:    minimize obj(x)
        INFO - 13:08:48:    with respect to x
        INFO - 13:08:48:    subject to constraints:
        INFO - 13:08:48:       cstr(x) <= 0.0
        INFO - 13:08:48:    over the design space:
        INFO - 13:08:48:       +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:       | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 13:08:48:       +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:       | x    |     -1.5    | 0.1666666666666667 |     1.5     | float |
        INFO - 13:08:48:       +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48: Solving optimization problem with algorithm SLSQP:
        INFO - 13:08:48:     10%|█         | 1/10 [00:00<00:00, 723.78 it/sec, obj=0.838]
        INFO - 13:08:48:     20%|██        | 2/10 [00:00<00:00, 372.96 it/sec, obj=2.88]
        INFO - 13:08:48:     30%|███       | 3/10 [00:00<00:00, 427.38 it/sec, obj=0.656]
        INFO - 13:08:48:     40%|████      | 4/10 [00:00<00:00, 388.87 it/sec, obj=0.639]
        INFO - 13:08:48:     50%|█████     | 5/10 [00:00<00:00, 369.19 it/sec, obj=0.616]
        INFO - 13:08:48:     60%|██████    | 6/10 [00:00<00:00, 359.75 it/sec, obj=0.615]
        INFO - 13:08:48:     70%|███████   | 7/10 [00:00<00:00, 347.74 it/sec, obj=0.615]
        INFO - 13:08:48:     80%|████████  | 8/10 [00:00<00:00, 342.73 it/sec, obj=0.615]
        INFO - 13:08:48:     90%|█████████ | 9/10 [00:00<00:00, 338.52 it/sec, obj=0.615]
        INFO - 13:08:48: Optimization result:
        INFO - 13:08:48:    Optimizer info:
        INFO - 13:08:48:       Status: None
        INFO - 13:08:48:       Message: Successive iterates of the objective function are closer than ftol_rel or ftol_abs. GEMSEO Stopped the driver
        INFO - 13:08:48:       Number of calls to the objective function by the optimizer: 10
        INFO - 13:08:48:    Solution:
        INFO - 13:08:48:       The solution is feasible.
        INFO - 13:08:48:       Objective: 0.6150998205402508
        INFO - 13:08:48:       Standardized constraints:
        INFO - 13:08:48:          cstr = -0.7883189092934597
        INFO - 13:08:48:       Design space:
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | x    |     -1.5    | 0.5773502416020033 |     1.5     | float |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48: *** End MDOScenario execution (time: 0:00:00.039507) ***
        INFO - 13:08:48:     60%|██████    | 6/10 [00:00<00:00, 22.97 it/sec, obj=0.615]
        INFO - 13:08:48:  
        INFO - 13:08:48: *** Start MDOScenario execution ***
        INFO - 13:08:48: MDOScenario
        INFO - 13:08:48:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 13:08:48:    MDO formulation: DisciplinaryOpt
        INFO - 13:08:48: Optimization problem:
        INFO - 13:08:48:    minimize obj(x)
        INFO - 13:08:48:    with respect to x
        INFO - 13:08:48:    subject to constraints:
        INFO - 13:08:48:       cstr(x) <= 0.0
        INFO - 13:08:48:    over the design space:
        INFO - 13:08:48:       +------+-------------+-------+-------------+-------+
        INFO - 13:08:48:       | Name | Lower bound | Value | Upper bound | Type  |
        INFO - 13:08:48:       +------+-------------+-------+-------------+-------+
        INFO - 13:08:48:       | x    |     -1.5    |  0.5  |     1.5     | float |
        INFO - 13:08:48:       +------+-------------+-------+-------------+-------+
        INFO - 13:08:48: Solving optimization problem with algorithm SLSQP:
        INFO - 13:08:48:     10%|█         | 1/10 [00:00<00:00, 758.46 it/sec, obj=0.625]
        INFO - 13:08:48:     20%|██        | 2/10 [00:00<00:00, 382.83 it/sec, obj=2.87]
        INFO - 13:08:48:     30%|███       | 3/10 [00:00<00:00, 437.00 it/sec, obj=0.616]
        INFO - 13:08:48:     40%|████      | 4/10 [00:00<00:00, 400.32 it/sec, obj=0.615]
        INFO - 13:08:48:     50%|█████     | 5/10 [00:00<00:00, 379.14 it/sec, obj=0.615]
        INFO - 13:08:48:     60%|██████    | 6/10 [00:00<00:00, 366.48 it/sec, obj=0.615]
        INFO - 13:08:48:     70%|███████   | 7/10 [00:00<00:00, 359.51 it/sec, obj=0.615]
        INFO - 13:08:48: Optimization result:
        INFO - 13:08:48:    Optimizer info:
        INFO - 13:08:48:       Status: None
        INFO - 13:08:48:       Message: Successive iterates of the objective function are closer than ftol_rel or ftol_abs. GEMSEO Stopped the driver
        INFO - 13:08:48:       Number of calls to the objective function by the optimizer: 8
        INFO - 13:08:48:    Solution:
        INFO - 13:08:48:       The solution is feasible.
        INFO - 13:08:48:       Objective: 0.6150998205402526
        INFO - 13:08:48:       Standardized constraints:
        INFO - 13:08:48:          cstr = -0.7883188285028959
        INFO - 13:08:48:       Design space:
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | x    |     -1.5    | 0.5773503115686811 |     1.5     | float |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48: *** End MDOScenario execution (time: 0:00:00.032174) ***
        INFO - 13:08:48:     70%|███████   | 7/10 [00:00<00:00, 23.67 it/sec, obj=0.615]
        INFO - 13:08:48:  
        INFO - 13:08:48: *** Start MDOScenario execution ***
        INFO - 13:08:48: MDOScenario
        INFO - 13:08:48:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 13:08:48:    MDO formulation: DisciplinaryOpt
        INFO - 13:08:48: Optimization problem:
        INFO - 13:08:48:    minimize obj(x)
        INFO - 13:08:48:    with respect to x
        INFO - 13:08:48:    subject to constraints:
        INFO - 13:08:48:       cstr(x) <= 0.0
        INFO - 13:08:48:    over the design space:
        INFO - 13:08:48:       +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:       | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 13:08:48:       +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:       | x    |     -1.5    | 0.8333333333333335 |     1.5     | float |
        INFO - 13:08:48:       +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48: Solving optimization problem with algorithm SLSQP:
        INFO - 13:08:48:     10%|█         | 1/10 [00:00<00:00, 741.17 it/sec, obj=0.745]
        INFO - 13:08:48:     20%|██        | 2/10 [00:00<00:00, 379.06 it/sec, obj=-0.875]
        INFO - 13:08:48:     30%|███       | 3/10 [00:00<00:00, 374.49 it/sec, obj=-0.267]
        INFO - 13:08:48:     40%|████      | 4/10 [00:00<00:00, 390.86 it/sec, obj=-0.809]
        INFO - 13:08:48:     50%|█████     | 5/10 [00:00<00:00, 419.75 it/sec, obj=-0.868]
        INFO - 13:08:48:     60%|██████    | 6/10 [00:00<00:00, 440.57 it/sec, obj=-0.874]
        INFO - 13:08:48:     70%|███████   | 7/10 [00:00<00:00, 428.16 it/sec, obj=-0.266]
        INFO - 13:08:48:     80%|████████  | 8/10 [00:00<00:00, 419.28 it/sec, obj=0.135]
        INFO - 13:08:48:     90%|█████████ | 9/10 [00:00<00:00, 412.83 it/sec, obj=0.577]
        INFO - 13:08:48:    100%|██████████| 10/10 [00:00<00:00, 426.79 it/sec, obj=0.288]
        INFO - 13:08:48: Optimization result:
        INFO - 13:08:48:    Optimizer info:
        INFO - 13:08:48:       Status: None
        INFO - 13:08:48:       Message: Maximum number of iterations reached. GEMSEO Stopped the driver
        INFO - 13:08:48:       Number of calls to the objective function by the optimizer: 12
        INFO - 13:08:48:    Solution:
        INFO - 13:08:48:       The solution is feasible.
        INFO - 13:08:48:       Objective: 0.7453703703703706
        INFO - 13:08:48:       Standardized constraints:
        INFO - 13:08:48:          cstr = -0.2499785665294918
        INFO - 13:08:48:       Design space:
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | x    |     -1.5    | 0.8333333333333335 |     1.5     | float |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48: *** End MDOScenario execution (time: 0:00:00.037508) ***
        INFO - 13:08:48:     80%|████████  | 8/10 [00:00<00:00, 23.84 it/sec, obj=0.745]
        INFO - 13:08:48:  
        INFO - 13:08:48: *** Start MDOScenario execution ***
        INFO - 13:08:48: MDOScenario
        INFO - 13:08:48:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 13:08:48:    MDO formulation: DisciplinaryOpt
        INFO - 13:08:48: Optimization problem:
        INFO - 13:08:48:    minimize obj(x)
        INFO - 13:08:48:    with respect to x
        INFO - 13:08:48:    subject to constraints:
        INFO - 13:08:48:       cstr(x) <= 0.0
        INFO - 13:08:48:    over the design space:
        INFO - 13:08:48:       +------+-------------+-------------------+-------------+-------+
        INFO - 13:08:48:       | Name | Lower bound |       Value       | Upper bound | Type  |
        INFO - 13:08:48:       +------+-------------+-------------------+-------------+-------+
        INFO - 13:08:48:       | x    |     -1.5    | 1.166666666666667 |     1.5     | float |
        INFO - 13:08:48:       +------+-------------+-------------------+-------------+-------+
        INFO - 13:08:48: Solving optimization problem with algorithm SLSQP:
        INFO - 13:08:48:     10%|█         | 1/10 [00:00<00:00, 611.33 it/sec, obj=1.42]
        INFO - 13:08:48:     20%|██        | 2/10 [00:00<00:00, 301.22 it/sec, obj=-0.875]
        INFO - 13:08:48:     30%|███       | 3/10 [00:00<00:00, 318.30 it/sec, obj=-0.267]
        INFO - 13:08:48:     40%|████      | 4/10 [00:00<00:00, 346.31 it/sec, obj=-0.809]
        INFO - 13:08:48:     50%|█████     | 5/10 [00:00<00:00, 374.10 it/sec, obj=-0.868]
        INFO - 13:08:48:     60%|██████    | 6/10 [00:00<00:00, 398.18 it/sec, obj=-0.874]
        INFO - 13:08:48:     70%|███████   | 7/10 [00:00<00:00, 386.05 it/sec, obj=-0.266]
        INFO - 13:08:48:     80%|████████  | 8/10 [00:00<00:00, 354.00 it/sec, obj=0.135]
        INFO - 13:08:48:     90%|█████████ | 9/10 [00:00<00:00, 354.60 it/sec, obj=0.577]
        INFO - 13:08:48:    100%|██████████| 10/10 [00:00<00:00, 369.59 it/sec, obj=0.288]
     WARNING - 13:08:48: Optimization found no feasible point !  The least infeasible point is selected.
        INFO - 13:08:48: Optimization result:
        INFO - 13:08:48:    Optimizer info:
        INFO - 13:08:48:       Status: None
        INFO - 13:08:48:       Message: Maximum number of iterations reached. GEMSEO Stopped the driver
        INFO - 13:08:48:       Number of calls to the objective function by the optimizer: 12
        INFO - 13:08:48:    Solution:
     WARNING - 13:08:48:       The solution is not feasible.
        INFO - 13:08:48:       Objective: 0.28811314244698893
        INFO - 13:08:48:       Standardized constraints:
        INFO - 13:08:48:          cstr = 0.1514407501016959
        INFO - 13:08:48:       Design space:
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | x    |     -1.5    | -1.252370379420967 |     1.5     | float |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48: *** End MDOScenario execution (time: 0:00:00.041520) ***
        INFO - 13:08:48:     90%|█████████ | 9/10 [00:00<00:00, 23.77 it/sec, obj=0.288]
        INFO - 13:08:48:  
        INFO - 13:08:48: *** Start MDOScenario execution ***
        INFO - 13:08:48: MDOScenario
        INFO - 13:08:48:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 13:08:48:    MDO formulation: DisciplinaryOpt
        INFO - 13:08:48: Optimization problem:
        INFO - 13:08:48:    minimize obj(x)
        INFO - 13:08:48:    with respect to x
        INFO - 13:08:48:    subject to constraints:
        INFO - 13:08:48:       cstr(x) <= 0.0
        INFO - 13:08:48:    over the design space:
        INFO - 13:08:48:       +------+-------------+-------+-------------+-------+
        INFO - 13:08:48:       | Name | Lower bound | Value | Upper bound | Type  |
        INFO - 13:08:48:       +------+-------------+-------+-------------+-------+
        INFO - 13:08:48:       | x    |     -1.5    |  1.5  |     1.5     | float |
        INFO - 13:08:48:       +------+-------------+-------+-------------+-------+
        INFO - 13:08:48: Solving optimization problem with algorithm SLSQP:
        INFO - 13:08:48:     10%|█         | 1/10 [00:00<00:00, 729.82 it/sec, obj=2.88]
        INFO - 13:08:48:     20%|██        | 2/10 [00:00<00:00, 351.37 it/sec, obj=-0.875]
        INFO - 13:08:48:     30%|███       | 3/10 [00:00<00:00, 357.56 it/sec, obj=-0.267]
        INFO - 13:08:48:     40%|████      | 4/10 [00:00<00:00, 393.54 it/sec, obj=-0.809]
        INFO - 13:08:48:     50%|█████     | 5/10 [00:00<00:00, 408.82 it/sec, obj=-0.868]
        INFO - 13:08:48:     60%|██████    | 6/10 [00:00<00:00, 428.72 it/sec, obj=-0.874]
        INFO - 13:08:48:     70%|███████   | 7/10 [00:00<00:00, 417.27 it/sec, obj=-0.266]
        INFO - 13:08:48:     80%|████████  | 8/10 [00:00<00:00, 400.54 it/sec, obj=0.135]
        INFO - 13:08:48:     90%|█████████ | 9/10 [00:00<00:00, 394.98 it/sec, obj=0.577]
        INFO - 13:08:48:    100%|██████████| 10/10 [00:00<00:00, 408.63 it/sec, obj=0.288]
     WARNING - 13:08:48: Optimization found no feasible point !  The least infeasible point is selected.
        INFO - 13:08:48: Optimization result:
        INFO - 13:08:48:    Optimizer info:
        INFO - 13:08:48:       Status: None
        INFO - 13:08:48:       Message: Maximum number of iterations reached. GEMSEO Stopped the driver
        INFO - 13:08:48:       Number of calls to the objective function by the optimizer: 12
        INFO - 13:08:48:    Solution:
     WARNING - 13:08:48:       The solution is not feasible.
        INFO - 13:08:48:       Objective: 0.28811314244587316
        INFO - 13:08:48:       Standardized constraints:
        INFO - 13:08:48:          cstr = 0.15144075010180735
        INFO - 13:08:48:       Design space:
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48:          | x    |     -1.5    | -1.252370379421268 |     1.5     | float |
        INFO - 13:08:48:          +------+-------------+--------------------+-------------+-------+
        INFO - 13:08:48: *** End MDOScenario execution (time: 0:00:00.039261) ***
        INFO - 13:08:48:    100%|██████████| 10/10 [00:00<00:00, 23.84 it/sec, obj=0.288]
        INFO - 13:08:48: Optimization result:
        INFO - 13:08:48:    Optimizer info:
        INFO - 13:08:48:       Status: None
        INFO - 13:08:48:       Message: None
        INFO - 13:08:48:       Number of calls to the objective function by the optimizer: 10
        INFO - 13:08:48:    Solution:
        INFO - 13:08:48:       The solution is feasible.
        INFO - 13:08:48:       Objective: 0.6150998205402495
        INFO - 13:08:48:       Standardized constraints:
        INFO - 13:08:48:          cstr = -0.7883188793606977
        INFO - 13:08:48:       Design space:
        INFO - 13:08:48:          +------+-------------+---------------------+-------------+-------+
        INFO - 13:08:48:          | Name | Lower bound |        Value        | Upper bound | Type  |
        INFO - 13:08:48:          +------+-------------+---------------------+-------------+-------+
        INFO - 13:08:48:          | x    |     -1.5    | -0.1666666666666667 |     1.5     | float |
        INFO - 13:08:48:          +------+-------------+---------------------+-------------+-------+
        INFO - 13:08:48: *** End DOEScenario execution (time: 0:00:00.433810) ***

    {'eval_jac': False, 'n_samples': 10, 'algo': 'fullfact'}



.. GENERATED FROM PYTHON SOURCE LINES 90-92

Plot the optimum objective for different x0
-------------------------------------------

.. GENERATED FROM PYTHON SOURCE LINES 92-93

.. code-block:: Python

    scenario_doe.post_process("BasicHistory", variable_names=["obj"], save=False, show=True)



.. image-sg:: /examples/scenario_adapter/images/sphx_glr_plot_multistart_example_001.png
   :alt: History plot
   :srcset: /examples/scenario_adapter/images/sphx_glr_plot_multistart_example_001.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    <gemseo.post.basic_history.BasicHistory object at 0x7f8ba227b130>




.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.667 seconds)


.. _sphx_glr_download_examples_scenario_adapter_plot_multistart_example.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_multistart_example.ipynb <plot_multistart_example.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_multistart_example.py <plot_multistart_example.py>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_