An active set algorithm for nonlinear optimization with polyhedral constraints
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Publication:341314
DOI10.1007/s11425-016-0300-6zbMath1349.90619arXiv1606.01992OpenAlexW2417740149MaRDI QIDQ341314
William W. Hager, Hongchao Zhang
Publication date: 16 November 2016
Published in: Science China. Mathematics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1606.01992
gradient projection algorithmactive set algorithmlocal and global convergencePASApolyhedral constrained optimization
Large-scale problems in mathematical programming (90C06) Nonconvex programming, global optimization (90C26) Complexity and performance of numerical algorithms (65Y20)
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Cites Work
- Unnamed Item
- Primal and dual active-set methods for convex quadratic programming
- An affine scaling method for optimization problems with polyhedral constraints
- On affine-scaling interior-point Newton methods for nonlinear minimization with bound constraints
- Convergence properties of trust region methods for linear and convex constraints
- A class of methods for solving large, convex quadratic programs subject to box constraints
- A new trust region algorithm for bound constrained minimization
- On the convergence of interior-reflective Newton methods for nonlinear minimization subject to bounds
- Family of projected descent methods for optimization problems with simple bounds
- A proportioning based algorithm with rate of convergence for bound constrained quadratic programming
- A trust region and affine scaling interior point method for nonconvex minimization with linear inequality constraints
- Superlinear and quadratic convergence of affine-scaling interior-point Newton methods for problems with simple bounds without strict complementarity assumption
- Methods for convex and general quadratic programming
- Projection onto a Polyhedron that Exploits Sparsity
- On the convergence of an active-set method for ℓ1minimization
- A Fast Algorithm for Sparse Reconstruction Based on Shrinkage, Subspace Optimization, and Continuation
- Gradient-Based Methods for Sparse Recovery
- Convergence of Trust Region Algorithms for Optimization with Bounds when Strict Complementarity Does Not Hold
- A New Active Set Algorithm for Box Constrained Optimization
- Projected gradient methods for linearly constrained problems
- Global Convergence of a Class of Trust Region Algorithms for Optimization with Simple Bounds
- On the Identification of Active Constraints
- Some continuity properties of polyhedral multifunctions
- Generalized equations and their solutions, part II: Applications to nonlinear programming
- On the Solution of Large Quadratic Programming Problems with Bound Constraints
- On the Goldstein-Levitin-Polyak gradient projection method
- Trust-Region Interior-Point SQP Algorithms for a Class of Nonlinear Programming Problems
- Global Convergence of Trust-region Interior-point Algorithms for Infinite-dimensional Nonconvex Minimization Subject to Pointwise Bounds
- Exposing Constraints
- Box Constrained Quadratic Programming with Proportioning and Projections
- An Active Set Newton Algorithm for Large-Scale Nonlinear Programs with Box Constraints
- Augmented Lagrangians with Adaptive Precision Control for Quadratic Programming with Simple Bounds and Equality Constraints
- Trust Region Methods
- Sparse Reconstruction by Separable Approximation
- A Nonmonotone Line Search Technique and Its Application to Unconstrained Optimization
- Newton's Method for Large Bound-Constrained Optimization Problems
- A Subspace, Interior, and Conjugate Gradient Method for Large-Scale Bound-Constrained Minimization Problems
- Projected Newton Methods for Optimization Problems with Simple Constraints
- A Truncated Newton Algorithm for Large Scale Box Constrained Optimization
- An Interior Trust Region Approach for Nonlinear Minimization Subject to Bounds
- Global and Finite Termination of a Two-Phase Augmented Lagrangian Filter Method for General Quadratic Programs
- Newton-Type Methods for Optimization and Variational Problems
- An Active-Set Method for Second-Order Conic-Constrained Quadratic Programming
- Convex programming in Hilbert space
- The conjugate gradient method in extremal problems
- The Gradient Projection Method under Mild Differentiability Conditions
