The global convergence of augmented Lagrangian methods based on NCP function in constrained nonconvex optimization
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Publication:1004224
DOI10.1016/j.amc.2008.10.015zbMath1160.65031OpenAlexW2026116392MaRDI QIDQ1004224
Publication date: 2 March 2009
Published in: Applied Mathematics and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.amc.2008.10.015
algorithmsnumerical resultsconstrained optimizationnonconvex optimizationnonlinear complementarity problemaugmented Lagrangian methodsdegenerate pointconvergence to KKT pointKarush-Kuhn-Tucker point
Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26) Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) (90C33)
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On local search in d.c. optimization problems, On the convergence of augmented Lagrangian methods for nonlinear semidefinite programming, On constrained optimization by interval arithmetic and interval order relations
Cites Work
- Unnamed Item
- On the convergence of the exponential multiplier method for convex programming
- Dual techniques for constrained optimization
- A globally convergent, implementable multiplier method with automatic penalty limitation
- Enlarging the region of convergence of Newton's method for constrained optimization
- Modified barrier functions (theory and methods)
- On the convergence rate for a penalty function method of exponential type
- Handbook of test problems in local and global optimization
- Extended convergence results for the method of multipliers for nonstrictly binding inequality constraints
- On the convergence of interior-reflective Newton methods for nonlinear minimization subject to bounds
- Local saddle points and convexification for nonconvex optimization problems
- Lagrange-type functions in constrained optimization
- Nonlinear rescaling vs. smoothing technique in convex optimization
- Convexification and existence of a saddle point in a \(p\)th-power reformulation for nonconvex constrained optimization.
- Zero duality gap for a class of nonconvex optimization problems
- On the twice differentiable cubic augmented Lagrangian
- A nonlinear Lagrangian based on Fischer-Burmeister NCP function
- Augmented Lagrangian methods under the constant positive linear dependence constraint qualification
- Numerical comparison of augmented Lagrangian algorithms for nonconvex problems
- Primal-dual nonlinear rescaling method with dynamic scaling parameter update
- Multiplier and gradient methods
- The multiplier method of Hestenes and Powell applied to convex programming
- An Augmented Lagrangian Function with Improved Exactness Properties
- Lagrange Multipliers and Optimality
- A Globally Convergent Augmented Lagrangian Algorithm for Optimization with General Constraints and Simple Bounds
- Unconstrained Lagrangians in Nonlinear Programming
- On the Convergence of Augmented Lagrangian Methods for Constrained Global Optimization
- On Augmented Lagrangian Methods with General Lower-Level Constraints
- Convergence properties of augmented Lagrangian methods for constrained global optimization
- Recursive quadratic programming methods based on the augmented lagrangian
- A globally convergent constrained quasi-Newton method with an augmented lagrangian type penalty function
- Combined Primal–Dual and Penalty Methods for Convex Programming
- A Globally Convergent Augmented Lagrangian Pattern Search Algorithm for Optimization with General Constraints and Simple Bounds
- An Interior Trust Region Approach for Nonlinear Minimization Subject to Bounds
- Convergence Properties of an Augmented Lagrangian Algorithm for Optimization with a Combination of General Equality and Linear Constraints
- On Saddle Points of Augmented Lagrangians for Constrained Nonconvex Optimization
- Augmented Lagrange Multiplier Functions and Duality in Nonconvex Programming
- The Zero Duality Gap Property and Lower Semicontinuity of the Perturbation Function
- A Unified Augmented Lagrangian Approach to Duality and Exact Penalization
- Existence of a saddle point in nonconvex constrained optimization.
