An Exact Augmented Lagrangian Function for Nonlinear Programming with Two-Sided Constraints
Computational Optimization and Applications
Partially Strictly Monotone and Nonlinear Penalty Functions for Constrained Mathematical Programs
Computational Optimization and Applications
Further Study on Augmented Lagrangian Duality Theory
Journal of Global Optimization
Mathematics of Operations Research
Convergence properties of augmented Lagrangian methods for constrained global optimization
Optimization Methods & Software - THE JOINT EUROPT-OMS CONFERENCE ON OPTIMIZATION, 4-7 JULY, 2007, PRAGUE, CZECH REPUBLIC, PART I
Unified theory of augmented Lagrangian methods for constrained global optimization
Journal of Global Optimization
A truncated Newton method in an augmented Lagrangian framework for nonlinear programming
Computational Optimization and Applications
Saddle points of general augmented Lagrangians for constrained nonconvex optimization
Journal of Global Optimization
On the convergence of augmented Lagrangian methods for nonlinear semidefinite programming
Journal of Global Optimization
A new class of exact penalty functions and penalty algorithms
Journal of Global Optimization
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In this paper we introduce a new exact augmented Lagrangian function for the solution of general nonlinear programming problems. For this Lagrangian function a complete equivalence between its unconstrained minimization on an open set and the solution of the original constrained problem can be established under mild assumptions and without requiring the boundedness of the feasible set of the constrained problem. Moreover we describe an unconstrained algorithmic model which is globally convergent toward KKT pairs of the original constrained problem. The algorithmic model can be endowed with a superlinear rate of convergence by a proper choice of the search direction in the unconstrained minimization, without requiring strict complementarity.