In process systems, selecting suitable sets of manipulated and controlled variables and the design of their interconnection, known as the control structure selection problem, is an important structural optimization problem. The operating performance of a plant depends on the control structure selected, as well as the characteristics of the disturbances acting on the plant. The economic penalty associated with the variability of main process variables close to active constraints was used in this work to develop a quantitative measure for the ranking of alternative control structures. The problem is formulated as a mixed integer nonlinear optimization problem of special structure, which was used for an algorithm to solve this problem to global optimality. The final formulation is a mixed integer linear problem for which effective solution methods are currently available. The validity and usefulness of the method are demonstrated through a number of case studies.