.. _model-single-solution_level_cost:

"""""""""""""""""""
solution_level_cost
"""""""""""""""""""


Cost estimates associated with a set of solution control values.


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



**Specification**

- *Alias:* None

- *Arguments:* REALLIST


**Description**


Simulation-based models may have an associated ``solution_level_control``,
which identifies a hierarchy of solution states, such as a set of mesh
discretizations from coarse to fine, a set of solver tolerances from
loose to tight, etc.  In algorithms that manage such a hierarchy and
perform optimal resource allocation among the solution states (e.g.,
multilevel Monte Carlo), it is important to estimate a set of costs
associated with each state.  These cost estimates can be relative,
such as in the example below (lowest cost normalized to 1.)

*Note:* a scalar solution cost can be specified without an associated
solution level control.  This is useful when employing a hierarchy of
model forms (each model has a scalar solution cost and no solution level
control) instead of a hierarchy of discretization levels (one model has
a vector-valued solution cost associated with multiple solution levels).



**Examples**



.. code-block::

    model,
     simulation
       solution_level_control = 'mesh_size'
       solution_level_cost = 1. 8. 64. 512. 4096.
    
    variables,
     uniform_uncertain = 9
       lower_bounds      =  9*-1.
       upper_bounds      =  9* 1.
     discrete_state_set
       integer = 1
             set_values = 4 8 16 32 64
             descriptors = 'mesh_size'




