Part 1 presented a systematic procedure to analyze the interaction of design and control at the process synthesis stage by incorporating both steady-state economic and open-loop controllability measures within a multiobjective mixed-integer nonlinear optimization problem. Part 2 applies this framework to study the design of a system consisting of an isothermal reactor followed by a distillation column, whose distillate stream recycles back to the reactor. For this particular flowsheet, the resulting optimization can be written as a nonlinear programming (NLP) problem. A comparison of alternative designs shows that leaving the reactor and recycle stream compositions as variables in the NLP significantly reduces the cost compared with the cost of designs when these compositions are fixed. Economic considerations drive the optimal solution toward a larger reactor with lower reactant composition and toward a stripper column with lower vapor boilup. The derivation of steady-state gain expressions relating the product compositions in the column to manipulated and disturbance variables allows the incorporation of controllability measures within the NLP. Generation of the noninferior solution sets shows the quantitative trade-off between the steady-state economic and controllability objectives. In general, process controllability measures improve as the reactor holdup decreases and as the number of trays in the column increases, but the opposite changes improve the disturbance controllability measures. Closed-loop dynamic simulations compare the responses of several designs identified in the optimization.