A New Efficient Method for Global Discrete Multilevel Optimization Combining Branch-and-Bound and Space-Mapping

This paper presents a new method to handle discrete or mixed constrained optimization problems based on a high-fidelity 3-D finite element computational model. The original idea aims to combine branch-and-bound method that is enabling to ensure a global optimal solution and space-mapping techniques that allow to speed-up the optimization procedure by aligning a fine model and a coarse model. These algorithms are applied to design optimally a safety isolating transformer with categorical and integer design variables.