Blurb::
Reuses the same seed value for multiple random sampling sets
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.
Topics::

Examples::

.. code-block::

    method
      sampling
        sample_type lhs
        samples = 10
        fixed_seed


Theory::

Faq::

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