Dakota Reference Manual: search_method

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search_method

Select a search method for Newton-based optimizers

## Specification

Alias: none

Argument(s): none

Child Keywords:

| Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description
--- | --- | --- | --- | ---
| Required (Choose One) | Line Search Method (Group 1) | value_based_line_search | Use only function values for line search
gradient_based_line_search | Set the search method to use the gradient
trust_region | Use trust region as the globalization strategy.
tr_pds | Use direct search as the local search in a trust region method

## Description

The `search_method` control is defined for all Newton-based optimizers and is used to select between `trust_region`, `gradient_based_line_search`, and `value_based_line_search` methods. The `gradient_based_line_search` option uses the line search method proposed by[63]. This option satisfies sufficient decrease and curvature conditions; whereas, `value_base_line_search` only satisfies the sufficient decrease condition. At each line search iteration, the `gradient_based_line_search` method computes the function and gradient at the trial point. Consequently, given expensive function evaluations, the `value_based_line_search` method is preferred to the `gradient_based_line_search` method. Each of these Newton methods additionally supports the `tr_pds` selection for unconstrained problems. This option performs a robust trust region search using pattern search techniques. Use of a line search is the default for bound-constrained and generally-constrained problems, and use of a `trust_region` search method is the default for unconstrained problems.