In the processing industry, there is the need to approach the operation of industrial equipment so they increase their energy efficiency, leading to more-economical and environmentally oriented processes. A feasible way to achieve these purposes lies in the optimal dynamic operation of industrial operations. In this work, we address the dynamic optimal operation of a highly energy-intensive industrial operation (distillation) under two common operating scenarios: start-up and steady-state transition operations. The start-up operations and steady-state transitions of a reactive distillation column were addressed in this paper by approaching the problem as a dynamic optimization problem. A detailed tray-by-tray model that considers internal tray hydraulics, but ignores vapor dynamics, was derived and used for calculations. Several manipulated variables were considered, besides the reboiler heat duty. The large scale nonlinear programming (NLP) problems generated from the application of the simultaneous dynamic optimization method were successfully solved with the use of an interior point optimizer (IPOPT). It was determined that, with the use of dynamic optimization, large time reductions can be obtained, when compared to empirical ramplike changes in the manipulated variables, thus reducing the amount of waste and energy consumption. Overall, when using optimal, rather than empirical dynamic operation policies, energy and raw material savings on the order of one order of magnitude, which clearly demonstrates that significant economic and environmental advantages can be achieved by approaching the dynamic operation of industrial processes as a formal dynamic optimization problem.