Dakota Reference Manual: hybrid

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hybrid

Strategy in which a set of methods synergistically seek an optimal design

## Specification

Alias: none

Argument(s): none

Child Keywords:

| Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description
--- | --- | --- | --- | ---
| Required (Choose One) | Hybrid Method Type (Group 1) | sequential | Methods are run one at a time, in sequence
embedded | A subordinate local method provides periodic refinements to a top-level global method
collaborative | Multiple methods run concurrently and share information

## Description

In a hybrid minimization method (`hybrid`), a set of methods synergistically seek an optimal design. The relationships among the methods are categorized as:

- collaborative
- embedded
- sequential

The goal in each case is to exploit the strengths of different optimization and nonlinear least squares algorithms at different stages of the minimization process. Global + local hybrids (e.g., genetic algorithms combined with nonlinear programming) are a common example in which the desire for identification of a global optimum is balanced with the need for efficient navigation to a local optimum.