New interval methods for constrained global optimization

branch-and-bound algorithms able to solve many global optimization
problems. In this talk I present new adaptive multisection rules
which enable the algorithm to choose the proper multisection type
depending on simple heuristic decision rules.
Moreover, for the selection of the next box to be subdivided, we
investigate new heuristic decision criteria. Both the adaptive
multisection and the subinterval selection rules seem to be
specially suitable for being used in inequality constrained global
optimization problems. The usefulness of these
new techniques is shown by computational studies.