- 1.
- that there is value in using the optimization to guide when and where to sample the objective to build an algebraic approximation and
- 2.
- that this should be done so in a way that pays some heed to the overall quality of the approximation.

In higher dimensions, we are not sanguine that good approximations of
the objective can be constructed over the entire design region. The
curse of dimensionality is likely to hold sway for all but the
simplest of objective functions. Nonetheless, we wish to avoid the
tendency of most derivative-based optimization techniques to find the
local minimizer nearest the initial trial point used to start the
optimization process. Furthermore, by attempting to
construct a global rather than a local approximation to the objective,
we can use such tools as analysis of variance (ANOVA) to discern other
information about the objective either before or after the
optimization process.

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