nonlinear multiple-input multiple-output (mimo) processes which are common in industrial plants are characterized by significant interactions and nonlinearities among their variables. thus, the tuning of several controllers in complex industrial plants is a challenge for process engineers and operators. this paper addresses the problem of simultaneously tuning n proportional-integral-derivative (pi/pid) controllers in a coupled multivariable process as a multi-criteria optimization problem. a multi objective genetic algorithm modified by a niching technique with castes formation is proposed to solve this problem. the optimization is carried out in two levels. in the first level a local function that considers both the integral time squared error (itse) and the minimum variance criteria is computed to separately evaluate the performance of each closed loop. thereafter, a global cost function that considers all the loops is used to compute a set of solutions (a set of pi/pid parameters) to the optimization problem. the proposed system was applied to the control of a fluid catalytic cracking (fcc) unit, and its performance was compared to dynamic matrix control (dmc). the results show the applicability and effectiveness of the proposed method.