1Blurb::
2Cost estimates associated with a set of solution control values.
3
4Description::
5Simulation-based models may have an associated \c solution_level_control,
6which identifies a hierarchy of solution states, such as a set of mesh
7discretizations from coarse to fine, a set of solver tolerances from
8loose to tight, etc.  In algorithms that manage such a hierarchy and
9perform optimal resource allocation among the solution states (e.g.,
10multilevel Monte Carlo), it is important to estimate a set of costs
11associated with each state.  These cost estimates can be relative,
12such as in the example below (lowest cost normalized to 1.)
13
14<b>Note:</b> a scalar solution cost can be specified without an associated
15solution level control.  This is useful when employing a hierarchy of
16model forms (each model has a scalar solution cost and no solution level
17control) instead of a hierarchy of discretization levels (one model has
18a vector-valued solution cost associated with multiple solution levels).
19
20Topics::
21
22Examples::
23\verbatim
24model,
25	simulation
26	  solution_level_control = 'mesh_size'
27	  solution_level_cost = 1. 8. 64. 512. 4096.
28
29variables,
30	uniform_uncertain = 9
31	  lower_bounds      =  9*-1.
32	  upper_bounds      =  9* 1.
33	discrete_state_set
34	  integer = 1
35      	  set_values = 4 8 16 32 64
36      	  descriptors = 'mesh_size'
37\endverbatim
38
39Theory::
40Faq::
41See_Also::
42