This work addresses the design of reactive distillation columns to produce ETBE, based on a detailed first-principles model that considers equilibrium and kinetic information, rigorous physical property data, and catalyst deactivation. An evolutionary algorithm is used to generate a sequence of feasible designs with improved characteristics in a sequential solution/optimisation strategy, by specifying the design variables (both integer and continuous) that characterise a particular column configuration. Two classes of optimisation algorithms are compared: genetic algorithms and particle swarm optimisation. The objective function considered is the gross annual profit. The results demonstrate that both algorithms are adequate to solve this design problem. The effect of catalyst deactivation included in the design stage played a determinant role in the optimal column specification. A post-design sensitivity analysis is developed to assess the quality of the solutions obtained, together with the individual effects of each design variable in the optimal configuration identified. (C) 2014 Elsevier Ltd. All rights reserved.