Nonmonotone Spectral Projected Gradient Methods on Convex Sets
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Summary
The classical projected gradient schemes are extended to include a nonmonotone steplength strategy that is based on the Grippo--Lampariello--Lucidi non monotone line search that is combined with the spectral gradient choice of steplENGTH to accelerate the convergence process.
- Type
- article
- Published
- 1999-08-01
- Cited by
- 1,087
- References
- 46
- Access
- Open access
- OpenAlex
- https://openalex.org/W1973734200
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:2991780
Keywords
Line search, Mathematics, Gradient method, Proximal Gradient Methods, Mathematical optimization
References
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- Lancelot: A FORTRAN Package for Large-Scale Nonlinear Optimization (Release A)
- Correction to the paper on global convergence of a class of trust region algorithms for optimization with simple bounds
- On Some Properties of Quadratic Programs with a Convex Quadratic Constraint
- A new trust region algorithm for bound constrained minimization
- A semidefinite framework for trust region subproblems with applications to large scale minimization
- Automatic differentiation and spectral projected gradient methods for optimal control problems
- The Barzilai and Borwein Gradient Method for the Large Scale Unconstrained Minimization Problem
- Constrained minimization methods
- Restricted optimization: a clue to a fast and accurate implementation of the Common Reflection Surface Stack method
- Convex programming in Hilbert space
- A constrained least squares regularization method for nonlinear ill-posed problems
- A globally convergent augmented Lagrangian algorithm for optimization with general constraints and simple bounds
- A nonmonotone line search technique for Newton's method
- The Gradient Projection Method under Mild Differentiability Conditions
- On the Barzilai and Borwein choice of steplength for the gradient method
- A D.C. Optimization Algorithm for Solving the Trust-Region Subproblem
- Mesh Independence for Nonlinear Least Squares Problems with Norm Constraints
- A New Matrix-Free Algorithm for the Large-Scale Trust-Region Subproblem
- Estimation of the Optical Constants and the Thickness of Thin Films Using Unconstrained Optimization
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