The minimum norm of a linear fractional transformation (LFT) over a structured set is computed using a branch and bound algorithm. This is a global optimization problem caused by the possibility of local minima. Several computationally efficient lower bounds for the minimum norm of the LFT are developed, and it is demonstrated that the success of the optimization, as measured by time-to-converge, largely depends on the quality of these bounds.