Multifidelity optimization stops letting cheap runs eat the budget: on DTMB 5415 the hull resistance falls further than the single-fidelity baseline
Multifidelity active learning now folds the choice of fidelity into the choice of where to sample, instead of fixing the location first. MF-CAS scores each candidate by the high-fidelity improvement opportunity per unit cost using decomposed uncertainty intervals; on the constrained 14-dimensional DTMB 5415 hull hydrodynamic optimization with a 100 equivalent-high-fidelity budget, its resistance reduction exceeds that of the single-fidelity LCB baseline, while the multifidelity LCB baseline barely improves on the initial design.