On memory gradient method with trust region for unconstrained optimization

DOI10.1007/s11075-005-9008-0zbMath1098.65067OpenAlexW1972586004MaRDI QIDQ2492798

Jie Shen, Zhen-Jun Shi

Publication date: 14 June 2006

Published in: Numerical Algorithms (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2027.42/45437

zbMATH Keywords

unconstrained optimizationglobal convergencenumerical resultstrust region methodsline search methodsmemory gradient method

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Interior-point methods (90C51)

Related Items

A memory gradient method based on the nonmonotone technique, The convergence of subspace trust region methods, A new variant of the memory gradient method for unconstrained optimization, Convergence of memory gradient methods, A new supermemory gradient method for unconstrained optimization problems, A nonmonotone supermemory gradient algorithm for unconstrained optimization, A memory gradient method for non-smooth convex optimization

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A gradient-related algorithm with inexact line searches
• Differential optimization techniques
• More test examples for nonlinear programming codes
• A new and dynamic method for unconstrained minimization
• Supermemory descent methods for unconstrained minimization
• A globally convergent version of the Polak-Ribière conjugate gradient method
• A note on minimization problems and multistep methods
• Introduction to global optimization
• A class of gradient unconstrained minimization algorithms with adaptive stepsize
• A class on nonmonotone stabilization methods in unconstrained optimization
• Memory gradient method for the minimization of functions
• Relation between the memory gradient method and the Fletcher-Reeves method
• Study on a supermemory gradient method for the minimization of functions
• Quadratically convergent algorithms and one-dimensional search schemes
• The Barzilai and Borwein Gradient Method for the Large Scale Unconstrained Minimization Problem
• A Trust Region Algorithm for Equality Constrained Minimization: Convergence Properties and Implementation
• Two-Point Step Size Gradient Methods
• Global Convergence Properties of Conjugate Gradient Methods for Optimization
• Gradient Method with Retards and Generalizations
• Numerical Optimization
• Global Convergence of a Class of Trust Region Algorithms for Optimization Using Inexact Projections on Convex Constraints
• One-step and multistep procedures for constrained minimization problems
• Conjugate Directions without Linear Searches
• Relaxed steepest descent and Cauchy-Barzilai-Borwein method