In this paper, a new approach is presented to perform multi-objective dynamic optimizations of novel batch distillation utilizing an evolutionary algorithm. The contribution is divided into two major parts. First, the development of an efficient hybrid evolutionary algorithm covering multi-objective mixed integer dynamic optimization problems is presented. The efficiency of the optimization solver is proven by several complex test problems. Second, the application of the algorithm is shown by the optimization of a middle vessel batch distillation. The challenging non-linear dynamic model, which takes the start-up phase into account, is solved in Aspen Custom Modeler. It could be proven that the proposed evolutionary algorithm can be applied to complex mathematical problems. Likewise the algorithm was found to successfully handle the optimization of middle a vessel batch distillation. The results show the feasibility of the proposed methodology and a significant increase in profitability of the process. (C) 2009 Elsevier Ltd. All rights reserved.