The convergence speed of interval methods for global optimization

Three particular algorithms from a class of interval subdivision methods for global optimization are studied. The theoretical upper bound on the convergence speed of Hansenʹs method is given. The three methods (by Hansen, Moore-Skelboe, and a new one with a random actual box selection rule) are compared numerically.