Terry Rockafellar, University of Washington, Augmented Lagrangian Methods and Local Duality in Nonconvex Optimization
ZoomAugmented Lagrangians were first employed in an algorithm for solving nonlinear programming problems with equality constraints. However, the approach was soon extended to inequality constraints and shown in the case of convex programming to correspond to applying the proximal point algorithm to solve a dual problem. Recent developments make it possible now to articulate that…