 When the objective function is a convex function, then any local minimum will also be a global minimum.There exist efficient numerical techniques for minimizing convex functions, such as interior-point methods.To solve problems, researchers may use algorithms that terminate in a finite number of steps, or iterative methods that converge to a solution (on some specified class of problems), or heuristics that may provide approximate solutions to some problems (although their iterates need not converge).