Another level of difficulty is reached when the optimization problem is subject to constraints in the decision or in the objective space, making some of the trade-off solutions potentially impossible to sample . As the optimizer needs samples to refine its knowledge of the infeasible regions, it might unknowingly suggest infeasible candidates to the HTE platform. This can be critical for HTE platforms, as attempted sampling of infeasible solutions might damage the platform itself. Therefore, an ideal optimization algorithm must not only (1) quickly find the PF location, but also Moreover, when the objectives are experimentally measured, the optimizer would also need to deal with fidelity/noise concerns in synthesis and characterization, which complicates the objective landscape.