The standard approach to deal with uncertainty in dynamic optimization is to take a conservative stand. Measurement-based optimization schemes allow reducing this conservatism by using measurements to compensate for the uncertainty. On the example of productivity optimization of a batch distillation column with a terminal quality constraint, various measurement-based optimization schemes are compared. They all use measurements to update the input either from batch-to-batch or within the batch. A novel mid-course correction scheme for satisfying the terminal constraint is proposed.