hybrid
Strategy in which a set of methods synergistically seek an optimal design
Specification
Alias: None
Arguments: None
Child Keywords:
Required/Optional |
Description of Group |
Dakota Keyword |
Dakota Keyword Description |
|---|---|---|---|
Required (Choose One) |
Hybrid Method Type |
Methods are run one at a time, in sequence |
|
A subordinate local method provides periodic refinements to a top-level global method |
|||
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.
