.. _method-global_evidence-sbgo:

""""
sbgo
""""


Use the surrogate based optimization method


.. toctree::
   :hidden:
   :maxdepth: 1

   method-global_evidence-sbgo-gaussian_process
   method-global_evidence-sbgo-use_derivatives
   method-global_evidence-sbgo-import_build_points_file
   method-global_evidence-sbgo-export_approx_points_file


**Specification**

- *Alias:* None

- *Arguments:* None


**Child Keywords:**

+-------------------------+--------------------+-------------------------------+---------------------------------------------+
| Required/Optional       | Description of     | Dakota Keyword                | Dakota Keyword Description                  |
|                         | Group              |                               |                                             |
+=========================+====================+===============================+=============================================+
| Optional                                     | `gaussian_process`__          | Gaussian Process surrogate model            |
+----------------------------------------------+-------------------------------+---------------------------------------------+
| Optional                                     | `use_derivatives`__           | Use derivative data to construct surrogate  |
|                                              |                               | models                                      |
+----------------------------------------------+-------------------------------+---------------------------------------------+
| Optional                                     | `import_build_points_file`__  | File containing points you wish to use to   |
|                                              |                               | build a surrogate                           |
+----------------------------------------------+-------------------------------+---------------------------------------------+
| Optional                                     | `export_approx_points_file`__ | Output file for surrogate model value       |
|                                              |                               | evaluations                                 |
+----------------------------------------------+-------------------------------+---------------------------------------------+

.. __: method-global_evidence-sbgo-gaussian_process.html
__ method-global_evidence-sbgo-use_derivatives.html
__ method-global_evidence-sbgo-import_build_points_file.html
__ method-global_evidence-sbgo-export_approx_points_file.html



**Description**


A surrogate-based optimization method will be used.  The surrogate
employed in ``sbo`` is a Gaussian process surrogate.

The main difference between ``ego`` and the
``sbo`` approach is the objective function being optimized.
``ego`` relies on an expected improvement function, while in
``sbo``, the optimization proceeds using an evolutionary
algorithm ( :dakkw:`method-coliny_ea`) on the Gaussian process surrogate:
it is a standard surrogate-based optimization. Also note that the
``sbo`` option can support optimization over discrete variables (the
discrete variables are relaxed) while ``ego`` cannot.

This is not the same as :dakkw:`method-surrogate_based_global`.