A new method with sufficient descent property for unconstrained optimization
From MaRDI portal
Publication:1725328
DOI10.1155/2014/940120zbMath1474.90518OpenAlexW2025400298WikidataQ59042988 ScholiaQ59042988MaRDI QIDQ1725328
Publication date: 14 February 2019
Published in: Abstract and Applied Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2014/940120
Nonconvex programming, global optimization (90C26) Numerical optimization and variational techniques (65K10) Methods of quasi-Newton type (90C53) Methods of reduced gradient type (90C52)
Cites Work
- Unnamed Item
- Another improved Wei-Yao-Liu nonlinear conjugate gradient method with sufficient descent property
- Sufficient descent directions in unconstrained optimization
- A simple sufficient descent method for unconstrained optimization
- \(n\)-step quadratic convergence of the MPRP method with a restart strategy
- A spectral PRP conjugate gradient methods for nonconvex optimization problem based on modified line search
- Convergence properties of the regularized Newton method for the unconstrained nonconvex optimization
- New nonlinear conjugate gradient formulas for large-scale unconstrained optimization problems
- The convergence properties of some new conjugate gradient methods
- A limited memory BFGS-type method for large-scale unconstrained optimization
- Two Modified Polak–Ribière–Polyak-Type Nonlinear Conjugate Methods with Sufficient Descent Property
- The Barzilai and Borwein Gradient Method for the Large Scale Unconstrained Minimization Problem
- A descent modified Polak–Ribière–Polyak conjugate gradient method and its global convergence
- Two-Point Step Size Gradient Methods
- Global Convergence Properties of Conjugate Gradient Methods for Optimization
- A Two-Term PRP-Based Descent Method
- Benchmarking optimization software with performance profiles.
This page was built for publication: A new method with sufficient descent property for unconstrained optimization