Test Results for an Interval Branch and BoundAlgorithm for

Various techniques have been proposed for incorporating constraints in interval branch and bound algorithms for global optimization. However, few reports of practical experience with these techniques have appeared to date. Such experimental results appear here. The underlying implementation includes use of an approximate optimizer combined with a careful tesselation process and rigorous veriication of feasibility. The experiments include comparison of methods of handling bound constraints and comparison of two methods for normalizing Lagrange mul-tipliers. Selected test problems from the Floudas / Pardalos monograph are used, as well as selected unconstrained test problems appearing in reports of interval branch and bound methods for unconstrained global optimization.