A computationally efficient framework is presented for dynamic optimization of batch distillation where chemical reaction and separation take place simultaneously. An objective to maximize the conversion of the limiting reactant dynamic optimization problem (maximum conversion problem) is formulated for a representative system, and parametric solutions of the problem are obtained. Polynomial curve fitting techniques are then applied to the results of the dynamic optimization problem. These polynomials are used to formulate a nonlinear algebraic maximum profit problem which can be solved extremely efficiently using a nonlinear optimization solver. This provides an efficient framework which can be used for on-line optimization of batch distillation within scheduling programs for batch processes. The method can also be easily extended to nonreactive batch distillation and to nonconventional batch distillation columns.