Hierarchical control via augmented Lagrangians

Saddle Points Theory of Two Classes of Augmented Lagrangians and Its Applications to Generalized Semi-infinite Programming

In this paper, we develop the sufficient conditions for the existence of local and global saddle points of two classes of augmented Lagrangian functions for nonconvex optimization problem with both equality and inequality constraints, which improve the corresponding results in available papers. The main feature of our sufficient condition for the existence of global saddle points is that we do ...

Semi–Monotonic Augmented Lagrangians for Optimal Control and Parameter Identification

Optimization and inverse problems governed with partial differential equations are often formulated as constrained nonlinear programming problems via the Lagrange formalism. The nonlinearity is treated using the sequential quadratic programming. A numerical solution then hinges on an efficient iterative method for the resulting saddle–point systems. In this paper we apply a semi–monotonic augme...

Abstract Convexity and Augmented Lagrangians

Convexity and Augmented Lagrangians Regina S. Burachik University of South Australia and University of Ballarat Workshop on Advances in Continuous Optimization Reykjavik, Iceland Friday June 30 and Saturday July 1, 2006

Penalty/Barrier Multiplier Methods for Convex Programming Problems

We study a class of methods for solving convex programs, which are based on nonquadratic Augmented Lagrangians for which the penalty parameters are functions of the multipliers. This gives rise to lagrangians which are nonlinear in the multipliers. Each augmented lagrangian is speciied by a choice of a penalty function ' and a penalty-updating function. The requirements on ' are mild, and allow...

Strict convex regularizations, proximal points and augmented lagrangians