Editing Mathematical optimization (section)

===Global convergence===
More generally, if the objective function is not a quadratic function, then many optimization methods use other methods to ensure that some subsequence of iterations converges to an optimal solution. The first and still popular method for ensuring convergence relies on [[line search]]es, which optimize a function along one dimension. A second and increasingly popular method for ensuring convergence uses [[trust region]]s. Both line searches and trust regions are used in modern methods of [[subgradient method|non-differentiable optimization]]. Usually, a global optimizer is much slower than advanced local optimizers (such as [[BFGS method|BFGS]]), so often an efficient global optimizer can be constructed by starting the local optimizer from different starting points.