In this contribution we analyze an industrial multi-component depropanizer model and show how to rewrite the original model to index-one formulation that is well adapted to dynamic optimization. The optimal control problems are then studied with the aim of determination of the optimal output trajectories for minimum changeover time requirements and disturbance rejection. The problems studied are typical situations that frequently occur in the industrial plant. The optimization method used is the control vector parametrization (CVP) which consists in converting the original problem into a non-linear programming (NLP) problem which was solved by a successive quadratic programming (SQP) method. The resulting profiles can be utilized as setpoints for the existing real plant control.