Global optimization

Global optimization is a branch of applied mathematics and numerical analysis that deals with the global optimization of a function or a set of functions according to some criteria. Typically, a set of bound and more general constraints is also present, and the decision variables are optimized considering also the constraints.

Global optimization is distinguished from regular optimization by its focus on finding the maximum or minimum over all input values, as opposed to finding local minima or maxima.

A common (standard) model form is the minimization of one real-valued function ${\displaystyle f}$ in the parameter-space ${\displaystyle {\vec {x}}\in P}$, or its specified subset ${\displaystyle {\vec {x}}\in D}$: here ${\displaystyle D}$ denotes the set defined by the constraints.

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