The Constraint Consensus Method for Finding Approximately Feasible Points in Nonlinear Programs

This paper develops a method for moving quickly and cheaply from an arbitrary initial point at an extreme distance from the feasible region to a point that is relatively near the feasible region of a nonlinearly constrained model. The method is a variant of a projection algorithm that is shown to be robust, even in the presence of nonconvex constraints and infeasibility. Empirical results are presented.