Dakota Reference Manual: optimize

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optimize

Surrogate is used in lieu of true model for mesh adaptive search

## Specification

Alias: none

Argument(s): none

## Description

When `optimize` is specified with `use_surrogate`, `mesh_adaptive_search` will use the surrogate in lieu of the true model and thus the true function is never invoked except to construct the surrogate.

Default Behavior

`optimize` is the default surrogate usage mode.

Expected Output

The user can expect to see both the number of true model evaluations and the number of approximation (i.e., surrogate) evaluations reported in the Dakota screen output. The former should equal the number of truth evaluations done for the surrogate construction.

## Examples

The following example shows the syntax used to set `use_surrogate` to `optimize`.

    method,
        mesh_adaptive_search
        model_pointer = 'SURROGATE'
        use_surrogate optimize

    model,
        id_model = 'SURROGATE'
        surrogate global
        polynomial quadratic
        dace_method_pointer = 'SAMPLING'

    variables,
        continuous_design = 3
          initial_point   -1.0    1.5   2.0
          upper_bounds    10.0   10.0  10.0
          lower_bounds   -10.0  -10.0 -10.0
          descriptors      'x1'  'x2'  'x3'
        discrete_design_range = 2
          initial_point      2     2
          lower_bounds       1     1
          upper_bounds       4     9
          descriptors      'y1'   'y2'
           discrete_design_set
             real = 2
               elements_per_variable = 4 5
               elements = 1.2 2.3 3.4 4.5 1.2 3.3 4.4 5.5 7.7
               descriptors      'y3'   'y4'
             integer = 2
               elements_per_variable = 2 2
               elements = 4 7 8 9
               descriptors      'z1'   'z2'

    method,
        id_method = 'SAMPLING'
        model_pointer = 'TRUTH'
        sampling
          samples = 55

    model,
        id_model = 'TRUTH'
        single
          interface_pointer = 'TRUE_FN'

    interface,
        id_interface = 'TRUE_FN'
           direct
          analysis_driver = 'text_book'

    responses,
        objective_functions = 1
        no_gradients
        no_hessians

The following will appear toward the end of the screen output when Dakota is run on this example. The number of true function evaluations includes only the 55 evaluations that were done to construct the surrogate (as specified in the SAMPLING method block).

    <<<<< Function evaluation summary (APPROX_INTERFACE): 221 total (221 new, 0 duplicate)
    <<<<< Function evaluation summary (TRUE_FN): 55 total (55 new, 0 duplicate)