# Global optimization

### From Glossary

Generally refers to mathematical programming without convexity assumptions, which
are NP-hard. In
general, there could be a local optimum that is not a global
optimum. Some authors use this term to imply the stronger condition
there are multiple local optima. Some
solution strategies are given as heuristic search
methods (including those that guarantee global convergence, such
as branch and bound). As a process associated with algorithm
design, some regard this simply as attempts to assure convergence
to a global optimum (unlike a purely local optimization procedure,
like steepest ascent). See the Glover's linearization.