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