An effective adaptive trust region algorithm for nonsmooth minimization
From MaRDI portal
Publication:1790684
DOI10.1007/s10589-018-9999-9zbMath1406.90099OpenAlexW2794690305MaRDI QIDQ1790684
Publication date: 2 October 2018
Published in: Computational Optimization and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10589-018-9999-9
global convergencesuperlinear convergencetrust region algorithmMoreau-Yosida regularizationnonsmooth problems
Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26)
Related Items
Adaptive three-term PRP algorithms without gradient Lipschitz continuity condition for nonconvex functions, Family weak conjugate gradient algorithms and their convergence analysis for nonconvex functions, Adaptive trust-region method on Riemannian manifold, A tensor trust-region model for nonlinear system, A conjugate gradient algorithm and its application in large-scale optimization problems and image restoration, A modified HZ conjugate gradient algorithm without gradient Lipschitz continuous condition for non convex functions
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A modified Hestenes and Stiefel conjugate gradient algorithm for large-scale nonsmooth minimizations and nonlinear equations
- A trust-region approach with novel filter adaptive radius for system of nonlinear equations
- An improved adaptive trust-region algorithm
- Algorithms for finite and semi-infinite Min-Max-Min problems using adaptive smoothing techniques
- Nonmonotone adaptive trust region method
- A BFGS trust-region method for nonlinear equations
- A smooth method for the finite minimax problem
- A new trust region algorithm for nonsmooth convex minimization
- A bundle-Newton method for nonsmooth unconstrained minimization
- Convergence of some algorithms for convex minimization
- A trust region algorithm for minimization of locally Lipschitzian functions
- Globally convergent BFGS method for nonsmooth convex optimization
- A new adaptive trust-region method for system of nonlinear equations
- A trust region method for nonsmooth convex optimization
- A globally convergent Newton method for convex \(SC^ 1\) minimization problems
- A new modified nonmonotone adaptive trust region method for unconstrained optimization
- Gradient trust region algorithm with limited memory BFGS update for nonsmooth convex minimization
- A derivative-free trust-region algorithm for composite nonsmooth optimization
- A modified Polak-Ribière-Polyak conjugate gradient algorithm for nonsmooth convex programs
- Nonmonotone adaptive trust region method with line search based on new diagonal updating
- A new nonsmooth trust region algorithm for locally Lipschitz unconstrained optimization problems
- A nonsmooth version of Newton's method
- A new trust region method for unconstrained optimization
- New quasi-Newton methods for unconstrained optimization problems
- An adaptive trust region method and its convergence
- THE BARZILAI AND BORWEIN GRADIENT METHOD WITH NONMONOTONE LINE SEARCH FOR NONSMOOTH CONVEX OPTIMIZATION PROBLEMS
- A new trust region method with adaptive radius for unconstrained optimization
- Introduction to Nonsmooth Optimization
- A descent algorithm for nonsmooth convex optimization
- The Conjugate Gradient Method and Trust Regions in Large Scale Optimization
- Optimization and nonsmooth analysis
- Trust Region Methods
- Convergence Analysis of Some Algorithms for Solving Nonsmooth Equations
- A Globally and Superlinearly Convergent Algorithm for Nonsmooth Convex Minimization
- Numerical methods for nondifferentiable convex optimization
- Survey of Bundle Methods for Nonsmooth Optimization
- A Method for Minimization of Quasidifferentiable Functions
- A New Algorithm for Unconstrained Optimization
- Benchmarking optimization software with performance profiles.
