We opted to use q-Noisy Expected Hypervolume Improvement (qNEHVI) acquisition function which is a state-of-the-art strategy for multi-objective optimization, and is also proven to be robust in handling observation noise . The qNEHVI acquisition function estimates the expected improvement of the HV of a suggested sample as predicted by the surrogate model.