.. 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 - 08:59:35:  
        INFO - 08:59:35: *** Start DOEScenario execution ***
        INFO - 08:59:35: DOEScenario
        INFO - 08:59:35:    Disciplines: MDOScenario_adapter
        INFO - 08:59:35:    MDO formulation: DisciplinaryOpt
        INFO - 08:59:35: Optimization problem:
        INFO - 08:59:35:    minimize obj(x)
        INFO - 08:59:35:    with respect to x
        INFO - 08:59:35:    subject to constraints:
        INFO - 08:59:35:       cstr(x) <= 0.0
        INFO - 08:59:35:    over the design space:
        INFO - 08:59:35:       +------+-------------+-------+-------------+-------+
        INFO - 08:59:35:       | Name | Lower bound | Value | Upper bound | Type  |
        INFO - 08:59:35:       +------+-------------+-------+-------------+-------+
        INFO - 08:59:35:       | x    |     -1.5    |  1.5  |     1.5     | float |
        INFO - 08:59:35:       +------+-------------+-------+-------------+-------+
        INFO - 08:59:35: Solving optimization problem with algorithm fullfact:
        INFO - 08:59:35:  
        INFO - 08:59:35: *** Start MDOScenario execution ***
        INFO - 08:59:35: MDOScenario
        INFO - 08:59:35:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 08:59:35:    MDO formulation: DisciplinaryOpt
        INFO - 08:59:35: Optimization problem:
        INFO - 08:59:35:    minimize obj(x)
        INFO - 08:59:35:    with respect to x
        INFO - 08:59:35:    subject to constraints:
        INFO - 08:59:35:       cstr(x) <= 0.0
        INFO - 08:59:35:    over the design space:
        INFO - 08:59:35:       +------+-------------+-------+-------------+-------+
        INFO - 08:59:35:       | Name | Lower bound | Value | Upper bound | Type  |
        INFO - 08:59:35:       +------+-------------+-------+-------------+-------+
        INFO - 08:59:35:       | x    |     -1.5    |  -1.5 |     1.5     | float |
        INFO - 08:59:35:       +------+-------------+-------+-------------+-------+
        INFO - 08:59:35: Solving optimization problem with algorithm SLSQP:
        INFO - 08:59:35:     10%|█         | 1/10 [00:00<00:00, 139.13 it/sec, obj=-0.875]
        INFO - 08:59:35:     20%|██        | 2/10 [00:00<00:00, 170.05 it/sec, obj=-0.267]
        INFO - 08:59:35:     30%|███       | 3/10 [00:00<00:00, 224.94 it/sec, obj=-0.809]
        INFO - 08:59:35:     40%|████      | 4/10 [00:00<00:00, 266.44 it/sec, obj=-0.868]
        INFO - 08:59:35:     50%|█████     | 5/10 [00:00<00:00, 301.52 it/sec, obj=-0.872]
        INFO - 08:59:35:     60%|██████    | 6/10 [00:00<00:00, 311.48 it/sec, obj=-0.265]
        INFO - 08:59:35:     70%|███████   | 7/10 [00:00<00:00, 319.95 it/sec, obj=0.136]
        INFO - 08:59:35:     80%|████████  | 8/10 [00:00<00:00, 325.84 it/sec, obj=0.579]
        INFO - 08:59:35:     90%|█████████ | 9/10 [00:00<00:00, 343.45 it/sec, obj=0.289]
        INFO - 08:59:35:    100%|██████████| 10/10 [00:00<00:00, 347.25 it/sec, obj=1.25]
     WARNING - 08:59:35: Optimization found no feasible point !  The least infeasible point is selected.
        INFO - 08:59:35: Optimization result:
        INFO - 08:59:35:    Optimizer info:
        INFO - 08:59:35:       Status: None
        INFO - 08:59:35:       Message: Maximum number of iterations reached. GEMSEO Stopped the driver
        INFO - 08:59:35:       Number of calls to the objective function by the optimizer: 12
        INFO - 08:59:35:    Solution:
     WARNING - 08:59:35:       The solution is not feasible.
        INFO - 08:59:35:       Objective: 0.2888129873625884
        INFO - 08:59:35:       Standardized constraints:
        INFO - 08:59:35:          cstr = 0.1513713660745195
        INFO - 08:59:35:       Design space:
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | x    |     -1.5    | -1.252181466244097 |     1.5     | float |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35: *** End MDOScenario execution (time: 0:00:00.044327) ***
        INFO - 08:59:35:     10%|█         | 1/10 [00:00<00:00, 19.76 it/sec, obj=0.289]
        INFO - 08:59:35:  
        INFO - 08:59:35: *** Start MDOScenario execution ***
        INFO - 08:59:35: MDOScenario
        INFO - 08:59:35:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 08:59:35:    MDO formulation: DisciplinaryOpt
        INFO - 08:59:35: Optimization problem:
        INFO - 08:59:35:    minimize obj(x)
        INFO - 08:59:35:    with respect to x
        INFO - 08:59:35:    subject to constraints:
        INFO - 08:59:35:       cstr(x) <= 0.0
        INFO - 08:59:35:    over the design space:
        INFO - 08:59:35:       +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:       | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 08:59:35:       +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:       | x    |     -1.5    | -1.166666666666667 |     1.5     | float |
        INFO - 08:59:35:       +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35: Solving optimization problem with algorithm SLSQP:
        INFO - 08:59:35:     10%|█         | 1/10 [00:00<00:00, 769.17 it/sec, obj=0.579]
        INFO - 08:59:35:     20%|██        | 2/10 [00:00<00:00, 392.01 it/sec, obj=-0.875]
        INFO - 08:59:35:     30%|███       | 3/10 [00:00<00:00, 389.43 it/sec, obj=-0.267]
        INFO - 08:59:35:     40%|████      | 4/10 [00:00<00:00, 426.56 it/sec, obj=-0.809]
        INFO - 08:59:35:     50%|█████     | 5/10 [00:00<00:00, 455.96 it/sec, obj=-0.868]
        INFO - 08:59:35:     60%|██████    | 6/10 [00:00<00:00, 476.77 it/sec, obj=-0.874]
        INFO - 08:59:35:     70%|███████   | 7/10 [00:00<00:00, 460.36 it/sec, obj=-0.266]
        INFO - 08:59:35:     80%|████████  | 8/10 [00:00<00:00, 448.37 it/sec, obj=0.135]
        INFO - 08:59:35:     90%|█████████ | 9/10 [00:00<00:00, 439.42 it/sec, obj=0.577]
        INFO - 08:59:35:    100%|██████████| 10/10 [00:00<00:00, 453.84 it/sec, obj=0.288]
     WARNING - 08:59:35: Optimization found no feasible point !  The least infeasible point is selected.
        INFO - 08:59:35: Optimization result:
        INFO - 08:59:35:    Optimizer info:
        INFO - 08:59:35:       Status: None
        INFO - 08:59:35:       Message: Maximum number of iterations reached. GEMSEO Stopped the driver
        INFO - 08:59:35:       Number of calls to the objective function by the optimizer: 12
        INFO - 08:59:35:    Solution:
     WARNING - 08:59:35:       The solution is not feasible.
        INFO - 08:59:35:       Objective: 0.28811314244670916
        INFO - 08:59:35:       Standardized constraints:
        INFO - 08:59:35:          cstr = 0.15144075010172386
        INFO - 08:59:35:       Design space:
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | x    |     -1.5    | -1.252370379421043 |     1.5     | float |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35: *** End MDOScenario execution (time: 0:00:00.036097) ***
        INFO - 08:59:35:     20%|██        | 2/10 [00:00<00:00, 22.70 it/sec, obj=0.288]
        INFO - 08:59:35:  
        INFO - 08:59:35: *** Start MDOScenario execution ***
        INFO - 08:59:35: MDOScenario
        INFO - 08:59:35:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 08:59:35:    MDO formulation: DisciplinaryOpt
        INFO - 08:59:35: Optimization problem:
        INFO - 08:59:35:    minimize obj(x)
        INFO - 08:59:35:    with respect to x
        INFO - 08:59:35:    subject to constraints:
        INFO - 08:59:35:       cstr(x) <= 0.0
        INFO - 08:59:35:    over the design space:
        INFO - 08:59:35:       +------+-------------+---------------------+-------------+-------+
        INFO - 08:59:35:       | Name | Lower bound |        Value        | Upper bound | Type  |
        INFO - 08:59:35:       +------+-------------+---------------------+-------------+-------+
        INFO - 08:59:35:       | x    |     -1.5    | -0.8333333333333334 |     1.5     | float |
        INFO - 08:59:35:       +------+-------------+---------------------+-------------+-------+
        INFO - 08:59:35: Solving optimization problem with algorithm SLSQP:
        INFO - 08:59:35:     10%|█         | 1/10 [00:00<00:00, 766.64 it/sec, obj=1.25]
        INFO - 08:59:35:     20%|██        | 2/10 [00:00<00:00, 387.07 it/sec, obj=-0.875]
        INFO - 08:59:35:     30%|███       | 3/10 [00:00<00:00, 448.83 it/sec, obj=1.01]
        INFO - 08:59:35:     40%|████      | 4/10 [00:00<00:00, 426.07 it/sec, obj=-0.875]
        INFO - 08:59:35:     50%|█████     | 5/10 [00:00<00:00, 453.40 it/sec, obj=0.819]
        INFO - 08:59:35:     60%|██████    | 6/10 [00:00<00:00, 433.22 it/sec, obj=-0.875]
        INFO - 08:59:35:     70%|███████   | 7/10 [00:00<00:00, 452.10 it/sec, obj=0.693]
        INFO - 08:59:35:     80%|████████  | 8/10 [00:00<00:00, 441.01 it/sec, obj=-0.875]
        INFO - 08:59:35:     90%|█████████ | 9/10 [00:00<00:00, 455.20 it/sec, obj=0.584]
        INFO - 08:59:35:    100%|██████████| 10/10 [00:00<00:00, 446.60 it/sec, obj=-0.875]
     WARNING - 08:59:35: Optimization found no feasible point !  The least infeasible point is selected.
        INFO - 08:59:35: Optimization result:
        INFO - 08:59:35:    Optimizer info:
        INFO - 08:59:35:       Status: None
        INFO - 08:59:35:       Message: Maximum number of iterations reached. GEMSEO Stopped the driver
        INFO - 08:59:35:       Number of calls to the objective function by the optimizer: 12
        INFO - 08:59:35:    Solution:
     WARNING - 08:59:35:       The solution is not feasible.
        INFO - 08:59:35:       Objective: 0.5837798748832244
        INFO - 08:59:35:       Standardized constraints:
        INFO - 08:59:35:          cstr = 0.19806414473664136
        INFO - 08:59:35:       Design space:
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | x    |     -1.5    | -1.165017254128868 |     1.5     | float |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35: *** End MDOScenario execution (time: 0:00:00.035460) ***
        INFO - 08:59:35:     30%|███       | 3/10 [00:00<00:00, 23.86 it/sec, obj=0.584]
        INFO - 08:59:35:  
        INFO - 08:59:35: *** Start MDOScenario execution ***
        INFO - 08:59:35: MDOScenario
        INFO - 08:59:35:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 08:59:35:    MDO formulation: DisciplinaryOpt
        INFO - 08:59:35: Optimization problem:
        INFO - 08:59:35:    minimize obj(x)
        INFO - 08:59:35:    with respect to x
        INFO - 08:59:35:    subject to constraints:
        INFO - 08:59:35:       cstr(x) <= 0.0
        INFO - 08:59:35:    over the design space:
        INFO - 08:59:35:       +------+-------------+-------+-------------+-------+
        INFO - 08:59:35:       | Name | Lower bound | Value | Upper bound | Type  |
        INFO - 08:59:35:       +------+-------------+-------+-------------+-------+
        INFO - 08:59:35:       | x    |     -1.5    |  -0.5 |     1.5     | float |
        INFO - 08:59:35:       +------+-------------+-------+-------------+-------+
        INFO - 08:59:35: Solving optimization problem with algorithm SLSQP:
        INFO - 08:59:35:     10%|█         | 1/10 [00:00<00:00, 796.79 it/sec, obj=1.38]
        INFO - 08:59:35:     20%|██        | 2/10 [00:00<00:00, 399.74 it/sec, obj=2.88]
        INFO - 08:59:35:     30%|███       | 3/10 [00:00<00:00, 453.39 it/sec, obj=1.23]
        INFO - 08:59:35:     40%|████      | 4/10 [00:00<00:00, 430.10 it/sec, obj=2.87]
        INFO - 08:59:35:     50%|█████     | 5/10 [00:00<00:00, 457.78 it/sec, obj=0.848]
        INFO - 08:59:35:     60%|██████    | 6/10 [00:00<00:00, 436.89 it/sec, obj=0.658]
        INFO - 08:59:35:     70%|███████   | 7/10 [00:00<00:00, 418.23 it/sec, obj=0.643]
        INFO - 08:59:35:     80%|████████  | 8/10 [00:00<00:00, 398.70 it/sec, obj=0.616]
        INFO - 08:59:35:     90%|█████████ | 9/10 [00:00<00:00, 389.56 it/sec, obj=0.615]
        INFO - 08:59:35:    100%|██████████| 10/10 [00:00<00:00, 382.85 it/sec, obj=0.615]
        INFO - 08:59:35: Optimization result:
        INFO - 08:59:35:    Optimizer info:
        INFO - 08:59:35:       Status: None
        INFO - 08:59:35:       Message: Maximum number of iterations reached. GEMSEO Stopped the driver
        INFO - 08:59:35:       Number of calls to the objective function by the optimizer: 13
        INFO - 08:59:35:    Solution:
        INFO - 08:59:35:       The solution is feasible.
        INFO - 08:59:35:       Objective: 0.6150998219543254
        INFO - 08:59:35:       Standardized constraints:
        INFO - 08:59:35:          cstr = -0.788285881879476
        INFO - 08:59:35:       Design space:
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | x    |     -1.5    | 0.5773788419679762 |     1.5     | float |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35: *** End MDOScenario execution (time: 0:00:00.039787) ***
        INFO - 08:59:35:     40%|████      | 4/10 [00:00<00:00, 23.97 it/sec, obj=0.615]
        INFO - 08:59:35:  
        INFO - 08:59:35: *** Start MDOScenario execution ***
        INFO - 08:59:35: MDOScenario
        INFO - 08:59:35:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 08:59:35:    MDO formulation: DisciplinaryOpt
        INFO - 08:59:35: Optimization problem:
        INFO - 08:59:35:    minimize obj(x)
        INFO - 08:59:35:    with respect to x
        INFO - 08:59:35:    subject to constraints:
        INFO - 08:59:35:       cstr(x) <= 0.0
        INFO - 08:59:35:    over the design space:
        INFO - 08:59:35:       +------+-------------+---------------------+-------------+-------+
        INFO - 08:59:35:       | Name | Lower bound |        Value        | Upper bound | Type  |
        INFO - 08:59:35:       +------+-------------+---------------------+-------------+-------+
        INFO - 08:59:35:       | x    |     -1.5    | -0.1666666666666667 |     1.5     | float |
        INFO - 08:59:35:       +------+-------------+---------------------+-------------+-------+
        INFO - 08:59:35: Solving optimization problem with algorithm SLSQP:
        INFO - 08:59:35:     10%|█         | 1/10 [00:00<00:00, 700.80 it/sec, obj=1.16]
        INFO - 08:59:35:     20%|██        | 2/10 [00:00<00:00, 384.76 it/sec, obj=2.87]
        INFO - 08:59:35:     30%|███       | 3/10 [00:00<00:00, 447.36 it/sec, obj=0.785]
        INFO - 08:59:35:     40%|████      | 4/10 [00:00<00:00, 406.92 it/sec, obj=2.88]
        INFO - 08:59:35:     50%|█████     | 5/10 [00:00<00:00, 421.33 it/sec, obj=0.644]
        INFO - 08:59:35:     60%|██████    | 6/10 [00:00<00:00, 402.40 it/sec, obj=0.624]
        INFO - 08:59:35:     70%|███████   | 7/10 [00:00<00:00, 389.28 it/sec, obj=0.615]
        INFO - 08:59:35:     80%|████████  | 8/10 [00:00<00:00, 381.30 it/sec, obj=0.615]
        INFO - 08:59:35:     90%|█████████ | 9/10 [00:00<00:00, 376.22 it/sec, obj=0.615]
        INFO - 08:59:35:    100%|██████████| 10/10 [00:00<00:00, 371.36 it/sec, obj=0.615]
        INFO - 08:59:35: Optimization result:
        INFO - 08:59:35:    Optimizer info:
        INFO - 08:59:35:       Status: None
        INFO - 08:59:35:       Message: Maximum number of iterations reached. GEMSEO Stopped the driver
        INFO - 08:59:35:       Number of calls to the objective function by the optimizer: 12
        INFO - 08:59:35:    Solution:
        INFO - 08:59:35:       The solution is feasible.
        INFO - 08:59:35:       Objective: 0.6150998205402495
        INFO - 08:59:35:       Standardized constraints:
        INFO - 08:59:35:          cstr = -0.7883188793606977
        INFO - 08:59:35:       Design space:
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | x    |     -1.5    | 0.5773502675245377 |     1.5     | float |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35: *** End MDOScenario execution (time: 0:00:00.040942) ***
        INFO - 08:59:35:     50%|█████     | 5/10 [00:00<00:00, 23.91 it/sec, obj=0.615]
        INFO - 08:59:35:  
        INFO - 08:59:35: *** Start MDOScenario execution ***
        INFO - 08:59:35: MDOScenario
        INFO - 08:59:35:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 08:59:35:    MDO formulation: DisciplinaryOpt
        INFO - 08:59:35: Optimization problem:
        INFO - 08:59:35:    minimize obj(x)
        INFO - 08:59:35:    with respect to x
        INFO - 08:59:35:    subject to constraints:
        INFO - 08:59:35:       cstr(x) <= 0.0
        INFO - 08:59:35:    over the design space:
        INFO - 08:59:35:       +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:       | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 08:59:35:       +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:       | x    |     -1.5    | 0.1666666666666667 |     1.5     | float |
        INFO - 08:59:35:       +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35: Solving optimization problem with algorithm SLSQP:
        INFO - 08:59:35:     10%|█         | 1/10 [00:00<00:00, 781.50 it/sec, obj=0.838]
        INFO - 08:59:35:     20%|██        | 2/10 [00:00<00:00, 396.32 it/sec, obj=2.88]
        INFO - 08:59:35:     30%|███       | 3/10 [00:00<00:00, 453.45 it/sec, obj=0.656]
        INFO - 08:59:35:     40%|████      | 4/10 [00:00<00:00, 414.02 it/sec, obj=0.639]
        INFO - 08:59:35:     50%|█████     | 5/10 [00:00<00:00, 394.08 it/sec, obj=0.616]
        INFO - 08:59:35:     60%|██████    | 6/10 [00:00<00:00, 380.67 it/sec, obj=0.615]
        INFO - 08:59:35:     70%|███████   | 7/10 [00:00<00:00, 367.55 it/sec, obj=0.615]
        INFO - 08:59:35:     80%|████████  | 8/10 [00:00<00:00, 362.14 it/sec, obj=0.615]
        INFO - 08:59:35:     90%|█████████ | 9/10 [00:00<00:00, 357.89 it/sec, obj=0.615]
        INFO - 08:59:35: Optimization result:
        INFO - 08:59:35:    Optimizer info:
        INFO - 08:59:35:       Status: None
        INFO - 08:59:35:       Message: Successive iterates of the objective function are closer than ftol_rel or ftol_abs. GEMSEO Stopped the driver
        INFO - 08:59:35:       Number of calls to the objective function by the optimizer: 10
        INFO - 08:59:35:    Solution:
        INFO - 08:59:35:       The solution is feasible.
        INFO - 08:59:35:       Objective: 0.6150998205402508
        INFO - 08:59:35:       Standardized constraints:
        INFO - 08:59:35:          cstr = -0.7883189092934597
        INFO - 08:59:35:       Design space:
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | x    |     -1.5    | 0.5773502416020033 |     1.5     | float |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35: *** End MDOScenario execution (time: 0:00:00.037247) ***
        INFO - 08:59:35:     60%|██████    | 6/10 [00:00<00:00, 24.14 it/sec, obj=0.615]
        INFO - 08:59:35:  
        INFO - 08:59:35: *** Start MDOScenario execution ***
        INFO - 08:59:35: MDOScenario
        INFO - 08:59:35:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 08:59:35:    MDO formulation: DisciplinaryOpt
        INFO - 08:59:35: Optimization problem:
        INFO - 08:59:35:    minimize obj(x)
        INFO - 08:59:35:    with respect to x
        INFO - 08:59:35:    subject to constraints:
        INFO - 08:59:35:       cstr(x) <= 0.0
        INFO - 08:59:35:    over the design space:
        INFO - 08:59:35:       +------+-------------+-------+-------------+-------+
        INFO - 08:59:35:       | Name | Lower bound | Value | Upper bound | Type  |
        INFO - 08:59:35:       +------+-------------+-------+-------------+-------+
        INFO - 08:59:35:       | x    |     -1.5    |  0.5  |     1.5     | float |
        INFO - 08:59:35:       +------+-------------+-------+-------------+-------+
        INFO - 08:59:35: Solving optimization problem with algorithm SLSQP:
        INFO - 08:59:35:     10%|█         | 1/10 [00:00<00:00, 801.82 it/sec, obj=0.625]
        INFO - 08:59:35:     20%|██        | 2/10 [00:00<00:00, 398.32 it/sec, obj=2.87]
        INFO - 08:59:35:     30%|███       | 3/10 [00:00<00:00, 457.44 it/sec, obj=0.616]
        INFO - 08:59:35:     40%|████      | 4/10 [00:00<00:00, 412.65 it/sec, obj=0.615]
        INFO - 08:59:35:     50%|█████     | 5/10 [00:00<00:00, 390.26 it/sec, obj=0.615]
        INFO - 08:59:35:     60%|██████    | 6/10 [00:00<00:00, 376.24 it/sec, obj=0.615]
        INFO - 08:59:35:     70%|███████   | 7/10 [00:00<00:00, 368.35 it/sec, obj=0.615]
        INFO - 08:59:35: Optimization result:
        INFO - 08:59:35:    Optimizer info:
        INFO - 08:59:35:       Status: None
        INFO - 08:59:35:       Message: Successive iterates of the objective function are closer than ftol_rel or ftol_abs. GEMSEO Stopped the driver
        INFO - 08:59:35:       Number of calls to the objective function by the optimizer: 8
        INFO - 08:59:35:    Solution:
        INFO - 08:59:35:       The solution is feasible.
        INFO - 08:59:35:       Objective: 0.6150998205402526
        INFO - 08:59:35:       Standardized constraints:
        INFO - 08:59:35:          cstr = -0.7883188285028959
        INFO - 08:59:35:       Design space:
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | x    |     -1.5    | 0.5773503115686811 |     1.5     | float |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35: *** End MDOScenario execution (time: 0:00:00.031072) ***
        INFO - 08:59:35:     70%|███████   | 7/10 [00:00<00:00, 24.83 it/sec, obj=0.615]
        INFO - 08:59:35:  
        INFO - 08:59:35: *** Start MDOScenario execution ***
        INFO - 08:59:35: MDOScenario
        INFO - 08:59:35:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 08:59:35:    MDO formulation: DisciplinaryOpt
        INFO - 08:59:35: Optimization problem:
        INFO - 08:59:35:    minimize obj(x)
        INFO - 08:59:35:    with respect to x
        INFO - 08:59:35:    subject to constraints:
        INFO - 08:59:35:       cstr(x) <= 0.0
        INFO - 08:59:35:    over the design space:
        INFO - 08:59:35:       +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:       | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 08:59:35:       +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:       | x    |     -1.5    | 0.8333333333333335 |     1.5     | float |
        INFO - 08:59:35:       +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35: Solving optimization problem with algorithm SLSQP:
        INFO - 08:59:35:     10%|█         | 1/10 [00:00<00:00, 757.37 it/sec, obj=0.745]
        INFO - 08:59:35:     20%|██        | 2/10 [00:00<00:00, 384.62 it/sec, obj=-0.875]
        INFO - 08:59:35:     30%|███       | 3/10 [00:00<00:00, 381.84 it/sec, obj=-0.267]
        INFO - 08:59:35:     40%|████      | 4/10 [00:00<00:00, 403.32 it/sec, obj=-0.809]
        INFO - 08:59:35:     50%|█████     | 5/10 [00:00<00:00, 433.49 it/sec, obj=-0.868]
        INFO - 08:59:35:     60%|██████    | 6/10 [00:00<00:00, 455.62 it/sec, obj=-0.874]
        INFO - 08:59:35:     70%|███████   | 7/10 [00:00<00:00, 442.82 it/sec, obj=-0.266]
        INFO - 08:59:35:     80%|████████  | 8/10 [00:00<00:00, 435.04 it/sec, obj=0.135]
        INFO - 08:59:35:     90%|█████████ | 9/10 [00:00<00:00, 429.11 it/sec, obj=0.577]
        INFO - 08:59:35:    100%|██████████| 10/10 [00:00<00:00, 444.16 it/sec, obj=0.288]
        INFO - 08:59:35: Optimization result:
        INFO - 08:59:35:    Optimizer info:
        INFO - 08:59:35:       Status: None
        INFO - 08:59:35:       Message: Maximum number of iterations reached. GEMSEO Stopped the driver
        INFO - 08:59:35:       Number of calls to the objective function by the optimizer: 12
        INFO - 08:59:35:    Solution:
        INFO - 08:59:35:       The solution is feasible.
        INFO - 08:59:35:       Objective: 0.7453703703703706
        INFO - 08:59:35:       Standardized constraints:
        INFO - 08:59:35:          cstr = -0.2499785665294918
        INFO - 08:59:35:       Design space:
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | x    |     -1.5    | 0.8333333333333335 |     1.5     | float |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35: *** End MDOScenario execution (time: 0:00:00.036433) ***
        INFO - 08:59:35:     80%|████████  | 8/10 [00:00<00:00, 24.96 it/sec, obj=0.745]
        INFO - 08:59:35:  
        INFO - 08:59:35: *** Start MDOScenario execution ***
        INFO - 08:59:35: MDOScenario
        INFO - 08:59:35:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 08:59:35:    MDO formulation: DisciplinaryOpt
        INFO - 08:59:35: Optimization problem:
        INFO - 08:59:35:    minimize obj(x)
        INFO - 08:59:35:    with respect to x
        INFO - 08:59:35:    subject to constraints:
        INFO - 08:59:35:       cstr(x) <= 0.0
        INFO - 08:59:35:    over the design space:
        INFO - 08:59:35:       +------+-------------+-------------------+-------------+-------+
        INFO - 08:59:35:       | Name | Lower bound |       Value       | Upper bound | Type  |
        INFO - 08:59:35:       +------+-------------+-------------------+-------------+-------+
        INFO - 08:59:35:       | x    |     -1.5    | 1.166666666666667 |     1.5     | float |
        INFO - 08:59:35:       +------+-------------+-------------------+-------------+-------+
        INFO - 08:59:35: Solving optimization problem with algorithm SLSQP:
        INFO - 08:59:35:     10%|█         | 1/10 [00:00<00:00, 796.19 it/sec, obj=1.42]
        INFO - 08:59:35:     20%|██        | 2/10 [00:00<00:00, 399.17 it/sec, obj=-0.875]
        INFO - 08:59:35:     30%|███       | 3/10 [00:00<00:00, 393.46 it/sec, obj=-0.267]
        INFO - 08:59:35:     40%|████      | 4/10 [00:00<00:00, 433.98 it/sec, obj=-0.809]
        INFO - 08:59:35:     50%|█████     | 5/10 [00:00<00:00, 463.55 it/sec, obj=-0.868]
        INFO - 08:59:35:     60%|██████    | 6/10 [00:00<00:00, 484.99 it/sec, obj=-0.874]
        INFO - 08:59:35:     70%|███████   | 7/10 [00:00<00:00, 465.97 it/sec, obj=-0.266]
        INFO - 08:59:35:     80%|████████  | 8/10 [00:00<00:00, 420.17 it/sec, obj=0.135]
        INFO - 08:59:35:     90%|█████████ | 9/10 [00:00<00:00, 416.18 it/sec, obj=0.577]
        INFO - 08:59:35:    100%|██████████| 10/10 [00:00<00:00, 430.65 it/sec, obj=0.288]
     WARNING - 08:59:35: Optimization found no feasible point !  The least infeasible point is selected.
        INFO - 08:59:35: Optimization result:
        INFO - 08:59:35:    Optimizer info:
        INFO - 08:59:35:       Status: None
        INFO - 08:59:35:       Message: Maximum number of iterations reached. GEMSEO Stopped the driver
        INFO - 08:59:35:       Number of calls to the objective function by the optimizer: 12
        INFO - 08:59:35:    Solution:
     WARNING - 08:59:35:       The solution is not feasible.
        INFO - 08:59:35:       Objective: 0.28811314244698893
        INFO - 08:59:35:       Standardized constraints:
        INFO - 08:59:35:          cstr = 0.1514407501016959
        INFO - 08:59:35:       Design space:
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | x    |     -1.5    | -1.252370379420967 |     1.5     | float |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35: *** End MDOScenario execution (time: 0:00:00.036881) ***
        INFO - 08:59:35:     90%|█████████ | 9/10 [00:00<00:00, 25.10 it/sec, obj=0.288]
        INFO - 08:59:35:  
        INFO - 08:59:35: *** Start MDOScenario execution ***
        INFO - 08:59:35: MDOScenario
        INFO - 08:59:35:    Disciplines: AnalyticDiscipline AnalyticDiscipline
        INFO - 08:59:35:    MDO formulation: DisciplinaryOpt
        INFO - 08:59:35: Optimization problem:
        INFO - 08:59:35:    minimize obj(x)
        INFO - 08:59:35:    with respect to x
        INFO - 08:59:35:    subject to constraints:
        INFO - 08:59:35:       cstr(x) <= 0.0
        INFO - 08:59:35:    over the design space:
        INFO - 08:59:35:       +------+-------------+-------+-------------+-------+
        INFO - 08:59:35:       | Name | Lower bound | Value | Upper bound | Type  |
        INFO - 08:59:35:       +------+-------------+-------+-------------+-------+
        INFO - 08:59:35:       | x    |     -1.5    |  1.5  |     1.5     | float |
        INFO - 08:59:35:       +------+-------------+-------+-------------+-------+
        INFO - 08:59:35: Solving optimization problem with algorithm SLSQP:
        INFO - 08:59:35:     10%|█         | 1/10 [00:00<00:00, 769.88 it/sec, obj=2.88]
        INFO - 08:59:35:     20%|██        | 2/10 [00:00<00:00, 399.44 it/sec, obj=-0.875]
        INFO - 08:59:35:     30%|███       | 3/10 [00:00<00:00, 396.10 it/sec, obj=-0.267]
        INFO - 08:59:35:     40%|████      | 4/10 [00:00<00:00, 432.51 it/sec, obj=-0.809]
        INFO - 08:59:35:     50%|█████     | 5/10 [00:00<00:00, 462.07 it/sec, obj=-0.868]
        INFO - 08:59:35:     60%|██████    | 6/10 [00:00<00:00, 483.98 it/sec, obj=-0.874]
        INFO - 08:59:35:     70%|███████   | 7/10 [00:00<00:00, 464.70 it/sec, obj=-0.266]
        INFO - 08:59:35:     80%|████████  | 8/10 [00:00<00:00, 452.79 it/sec, obj=0.135]
        INFO - 08:59:35:     90%|█████████ | 9/10 [00:00<00:00, 443.88 it/sec, obj=0.577]
        INFO - 08:59:35:    100%|██████████| 10/10 [00:00<00:00, 456.78 it/sec, obj=0.288]
     WARNING - 08:59:35: Optimization found no feasible point !  The least infeasible point is selected.
        INFO - 08:59:35: Optimization result:
        INFO - 08:59:35:    Optimizer info:
        INFO - 08:59:35:       Status: None
        INFO - 08:59:35:       Message: Maximum number of iterations reached. GEMSEO Stopped the driver
        INFO - 08:59:35:       Number of calls to the objective function by the optimizer: 12
        INFO - 08:59:35:    Solution:
     WARNING - 08:59:35:       The solution is not feasible.
        INFO - 08:59:35:       Objective: 0.28811314244587316
        INFO - 08:59:35:       Standardized constraints:
        INFO - 08:59:35:          cstr = 0.15144075010180735
        INFO - 08:59:35:       Design space:
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | Name | Lower bound |       Value        | Upper bound | Type  |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35:          | x    |     -1.5    | -1.252370379421268 |     1.5     | float |
        INFO - 08:59:35:          +------+-------------+--------------------+-------------+-------+
        INFO - 08:59:35: *** End MDOScenario execution (time: 0:00:00.035603) ***
        INFO - 08:59:35:    100%|██████████| 10/10 [00:00<00:00, 25.28 it/sec, obj=0.288]
        INFO - 08:59:35: Optimization result:
        INFO - 08:59:35:    Optimizer info:
        INFO - 08:59:35:       Status: None
        INFO - 08:59:35:       Message: None
        INFO - 08:59:35:       Number of calls to the objective function by the optimizer: 10
        INFO - 08:59:35:    Solution:
        INFO - 08:59:35:       The solution is feasible.
        INFO - 08:59:35:       Objective: 0.6150998205402495
        INFO - 08:59:35:       Standardized constraints:
        INFO - 08:59:35:          cstr = -0.7883188793606977
        INFO - 08:59:35:       Design space:
        INFO - 08:59:35:          +------+-------------+---------------------+-------------+-------+
        INFO - 08:59:35:          | Name | Lower bound |        Value        | Upper bound | Type  |
        INFO - 08:59:35:          +------+-------------+---------------------+-------------+-------+
        INFO - 08:59:35:          | x    |     -1.5    | -0.1666666666666667 |     1.5     | float |
        INFO - 08:59:35:          +------+-------------+---------------------+-------------+-------+
        INFO - 08:59:35: *** End DOEScenario execution (time: 0:00:00.409205) ***

    {'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 0x7f8ae7bb9a00>




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

   **Total running time of the script:** (0 minutes 0.633 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>`_