Adaptive three-term PRP algorithms without gradient Lipschitz continuity condition for nonconvex functions
From MaRDI portal
Publication:2163450
DOI10.1007/s11075-022-01257-3zbMath1496.65080OpenAlexW4206673622WikidataQ112879567 ScholiaQ112879567MaRDI QIDQ2163450
Mengxiang Zhang, Heshu Yang, Gong Lin Yuan
Publication date: 10 August 2022
Published in: Numerical Algorithms (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11075-022-01257-3
global convergenceconjugate gradientsufficient descent propertynonconvex functionsgradient Lipschitz continuity condition
Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26) Methods of reduced gradient type (90C52)
Related Items
Uses Software
Cites Work
- Unnamed Item
- 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 conjugate gradient method with descent direction for unconstrained optimization
- The convergence properties of some new conjugate gradient methods
- Efficient generalized conjugate gradient algorithms. I: Theory
- Modified nonlinear conjugate gradient methods with sufficient descent property for large-scale optimization problems
- BFGS trust-region method for symmetric nonlinear equations
- A modified PRP conjugate gradient method
- A new adaptive trust region algorithm for optimization problems
- An adaptive trust region algorithm for large-residual nonsmooth least squares problems
- A novel parameter estimation method for muskingum model using new Newton-type trust region algorithm
- A conjugate gradient algorithm under Yuan-Wei-Lu line search technique for large-scale minimization optimization models
- An effective adaptive trust region algorithm for nonsmooth minimization
- A conjugate gradient algorithm for large-scale nonlinear equations and image restoration problems
- Adaptive scaling damped BFGS method without gradient Lipschitz continuity
- The modified PRP conjugate gradient algorithm under a non-descent line search and its application in the Muskingum model and image restoration problems
- A modified Polak-Ribière-Polyak conjugate gradient algorithm for nonsmooth convex programs
- The PRP conjugate gradient algorithm with a modified WWP line search and its application in the image restoration problems
- The global convergence of the Polak-Ribière-Polyak conjugate gradient algorithm under inexact line search for nonconvex functions
- A three-terms Polak-Ribière-Polyak conjugate gradient algorithm for large-scale nonlinear equations
- An efficient projection-based algorithm without Lipschitz continuity for large-scale nonlinear pseudo-monotone equations
- Convergence Properties of Algorithms for Nonlinear Optimization
- A new trust-region method with line search for solving symmetric nonlinear equations
- A descent modified Polak–Ribière–Polyak conjugate gradient method and its global convergence
- Algorithm 851
- Descent Property and Global Convergence of the Fletcher—Reeves Method with Inexact Line Search
- Global Convergence Properties of Conjugate Gradient Methods for Optimization
- Convergence Properties of the BFGS Algoritm
- A Nonlinear Conjugate Gradient Method with a Strong Global Convergence Property
- A New Conjugate Gradient Method with Guaranteed Descent and an Efficient Line Search
- Function minimization by conjugate gradients
- Convergence Conditions for Ascent Methods
- Convergence Conditions for Ascent Methods. II: Some Corrections
- On Steepest Descent
- The conjugate gradient method in extremal problems
- Methods of conjugate gradients for solving linear systems
- A method for the solution of certain non-linear problems in least squares