This paper provides the triple-objective-function optimization results for the catalytic membrane reactors, including one for methanol synthesis and one for hydrogen generation. A 1-D, non-isothermal model, which takes into account the intra-particle diffusion for the catalyst, and the elitist nondominated sorting genetic algorithm (NSGA-II) for the multi-objective optimization are adopted. Optimal solutions for methanol synthesis and hydrogen generation systems show distinctive feature. One is randomly scattered and the other is linearly spread out in the Pareto plot. Solution characteristics in terms of variable distribution are quite different for the two systems. Device size, including membrane area and membrane size, shows effects both on the optimal solutions and on the correlation relations between objective functions and variables.