Blurb::
Strategy in which a set of methods synergistically seek an optimal design
Description::
In a hybrid minimization method (\c hybrid), a set of methods
synergistically seek an optimal design. The relationships among the
methods are categorized as:
\li collaborative
\li embedded
\li 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.



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