1. In a computing device hosting a technical computing environment used to process constrained optimization problems, a computer-implemented method of performing constrained optimization, comprising: providing a first population of a plurality of individuals for an optimization problem for a modeled system, the optimization problem including non-linear constraints, linear constraints and bound constraints, the individuals being individual solutions to the optimization problem; formulating a sub-problem from the optimization problem that excludes the linear and bound constraints and includes the non-linear constraints; solving, using the computing device, the sub-problem using a penalty parameter and at least one Lagrange parameter estimate to solve the optimization problem; generating, based on the solution to the sub-problem, a second population of individuals; storing the second population in a computer-readable storage medium, the second population available for use with the modeled system; minimizing, using the computing device, a sequence of the sub-problem to an approximate solution; determining, using the computing device, whether the approximate solution to the sub-problem is minimized to a pre-determined accuracy and whether the approximate solution to the sub-problem satisfies a feasibility condition; increasing, using the computing device, said at least one Lagrangian parameter estimate based on a determination that the approximate solution to the sub-problem is minimized to the pre-determined accuracy and that the approximate solution to the sub-problem satisfies the feasibility condition; and increasing, using the computing device, the penalty parameter in the sub-problem based on a determination that the sub-problem is not minimized to the pre-determined accuracy or that the sub-problem does not satisfy the feasibility condition.