.. _method-approximate_control_variate-fixed_seed:

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fixed_seed
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Reuses the same seed value for multiple random sampling sets


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



**Specification**

- *Alias:* None

- *Arguments:* None

- *Default:* not fixed; pattern varies run-to-run


**Description**


The ``fixed_seed`` flag is relevant if multiple sampling sets will be
generated over the coarse of a Dakota analysis. This occurs when using
advance methods (e.g., surrogate-based optimization, optimization
under uncertainty).  The same seed value is reused for each of these
multiple sampling sets, which can be important for reducing
variability in the sampling results.

*Default Behavior*

The default behavior is to not use a fixed seed, as the repetition of
the same sampling pattern can result in a modeling weakness that an
optimizer could potentially exploit (resulting in actual reliabilities
that are lower than the estimated reliabilities).  For repeatable
studies, the ``seed`` must also be specified.



**Examples**



.. code-block::

    method
      sampling
        sample_type lhs
        samples = 10
        fixed_seed