A derivative-free PRP method for solving large-scale nonlinear systems of equations and its global convergence
From MaRDI portal
Publication:5746712
DOI10.1080/10556788.2013.816306zbMath1282.90180OpenAlexW2073335853MaRDI QIDQ5746712
Publication date: 7 February 2014
Published in: Optimization Methods and Software (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/10556788.2013.816306
Related Items (9)
A Dai-Liao conjugate gradient method via modified secant equation for system of nonlinear equations ⋮ A Five-Parameter Class of Derivative-Free Spectral Conjugate Gradient Methods for Systems of Large-Scale Nonlinear Monotone Equations ⋮ A derivative-free Liu-Storey method for solving large-scale nonlinear systems of equations ⋮ A Riemannian derivative-free Polak-Ribiére-Polyak method for tangent vector field ⋮ Computing the largest H-eigenvalue of large-scale tensors generated from directed hypergraphs ⋮ A nonmonotone PRP conjugate gradient method for solving square and under-determined systems of equations ⋮ A modified PRP-type conjugate gradient projection algorithm for solving large-scale monotone nonlinear equations with convex constraint ⋮ Globally convergent diagonal Polak-Ribière-Polyak like algorithm for nonlinear equations ⋮ A NEW DERIVATIVE-FREE CONJUGATE GRADIENT METHOD FOR LARGE-SCALE NONLINEAR SYSTEMS OF EQUATIONS
Cites Work
- Globally convergent inexact quasi-Newton methods for solving nonlinear systems
- Superlinear convergence of a Newton-type algorithm for monotone equations
- A derivative-free method for solving large-scale nonlinear systems of equations
- Recent progress in the global convergence of quasi-Newton methods for nonlinear equations
- A Globally Convergent Newton-GMRES Subspace Method for Systems of Nonlinear Equations
- A descent modified Polak–Ribière–Polyak conjugate gradient method and its global convergence
- A Family of Quasi-Newton Methods for Nonlinear Equations with Direct Secant Updates of Matrix Factorizations
- Global Convergence Properties of Conjugate Gradient Methods for Optimization
- Convergence Theory of Nonlinear Newton–Krylov Algorithms
- CUTE
- A nonmonotone hybrid method for nonlinear systems∗
- A Nonmonotone Line Search Technique and Its Application to Unconstrained Optimization
- Nonmonotone Spectral Methods for Large-Scale Nonlinear Systems
- A Globally and Superlinearly Convergent Gauss--Newton-Based BFGS Method for Symmetric Nonlinear Equations
- A Nonmonotone Line Search Technique for Newton’s Method
- A derivative-free nonmonotone line search and its application to the spectral residual method
- A Two-Term PRP-Based Descent Method
- Spectral residual method without gradient information for solving large-scale nonlinear systems of equations
- The conjugate gradient method in extremal problems
- Benchmarking optimization software with performance profiles.
This page was built for publication: A derivative-free PRP method for solving large-scale nonlinear systems of equations and its global convergence
