  Multi-objective optimization is important for particle accelerators where
various competing objectives must be satisfied routinely such as, for example,
transverse emittance vs bunch length. We develop and demonstrate an online
multi-time scale multi-objective optimization algorithm that performs real time
feedback on particle accelerators. We demonstrate the ability to simultaneously
minimize the emittance and maintain a reference trajectory of a beam in the
electron beamline in CERN's Advanced Proton Driven Plasma Wakefield
Acceleration Experiment (AWAKE).
