This work presents two stochastic op- timization methods to perform the integrated syn- thesis and design of an activated sludge process. The process synthesis and design are carried out simul- taneously with the control system design to obtain the most economical plant which satisfies the desired control system performance. The mathematical for- mulation of this objective translates the process su- perstructure into a mixed-integer optimization prob- lem with non-linear constraints and dynamical- performance-indices evaluations. The proposed sto- chastic optimization algorithms, namely simulated annealing and a real-coded genetic algorithm, are valid alternatives to classical optimization techniques for the solution of such complex problems. The re- sults are encouraging for future applications, be- cause the easy implementation and the quality of the solutions obtained make not only possible but practi- cal the solution of the integrated synthesis and design problem.