Bayesian Optimisation under State-Preservation Constraints
The method addresses constrained Bayesian optimization by pre-computing a linear approximation of state-preservation constraints. It creates a proposal geometry based on this linear region, which is then used to efficiently sample promising designs within the optimization loop. This significantly improves sample efficiency over standard constrained BO methods.