Multi-objective bayesian optimisation and its applications

This thesis has sought to show how multi-objective Bayesian optimisation can be extended and applied to a variety of real-world problems. To this end, we have identified several unique aspects of the problems and suggested solutions accordingly. The developed methods have broad applicability in fields such as engineering design and machine learning. It has been shown that multi-objective Bayesian optimisation, as a sample-efficient optimisation method, can be an effective solution in many multi-objective optimisation scenarios.