In this section we outline some basic techniques
involving * deterministic* algorithms
for finding * local* minima of
multivariate functions whose arguments are continuous and on which
no restrictions are imposed. For constrained problems, techniques
are based on those for unconstrained problems, and we mention only
general approaches to them at the end of this section. It should be
emphasized that finding the * global* minimum is an entirely different,
and more challenging, problem which will not be
addressed here.
Basically, stochastic methods
are better suited at this time for
large-scale global optimization (see Figure 4) and some appropriate
algorithms will be outlined in Section 4.

Figure 4: The Structure of Local and Global Minimization Algorithms.