Numerical experiments with one-dimensional adaptive cubic algorithm

AbstractA code and some numerical experiments with a one-dimensional cubic algorithm are presented. It is demonstrated that the algorithm is applicable for full global optimization of a large class of functions including discontinuous and unbounded functions. Experiments with such functions show that successive runs yield monotonically improving results which descend onto the set of all global optimizers, if the sequence of experimental runs is properly organized