A nonmonotone adaptive trust region method for unconstrained optimization based on conic model

DOI10.1016/j.amc.2010.10.043zbMath1210.65123OpenAlexW2063762761MaRDI QIDQ618131

Shao-Jian Qu, Jian Zhang, Ke-Cun Zhang

Publication date: 14 January 2011

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2010.10.043

zbMATH Keywords

algorithmsunconstrained optimizationconvergencenumerical resultstrust region methodline searchconic modeladaptivenonmonotone technique

Mathematics Subject Classification ID

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

Related Items (3)

A nonmonotone trust region method based on simple conic models for unconstrained optimization ⋮ A nonmonotone weighting self-adaptive trust region algorithm for unconstrained nonconvex optimization ⋮ A novel self-adaptive trust region algorithm for unconstrained optimization

Uses Software

• minpack

Cites Work

• A nonmonotone trust region method for unconstrained optimization
• A nonmonotone trust-region method of conic model for unconstrained optimization
• Nonmonotone adaptive trust-region method for unconstrained optimization problems
• A nonmonotone adaptive trust region method and its convergence
• Nonmonotone trust region method for solving optimization problems
• Deriving collinear scaling algorithms as extensions of quasi-Newton methods and the local convergence of DFP- and BFGS-related collinear scaling algorithms
• Superlinearly convergent trust-region method without the assumption of positive-definite Hessian
• An adaptive trust region method and its convergence
• An adaptive approach of conic trust-region method for unconstrained optimization problems
• An adaptive conic trust-region method for unconstrained optimization
• On the global convergence of trust region algorithms for unconstrained minimization
• A Family of Trust-Region-Based Algorithms for Unconstrained Minimization with Strong Global Convergence Properties
• Conic Approximations and Collinear Scalings for Optimizers
• The Q-Superlinear Convergence of a Collinear Scaling Algorithm for Unconstrained Optimization
• Testing Unconstrained Optimization Software
• Automatic Determination of an Initial Trust Region in Nonlinear Programming
• A Nonmonotone Line Search Technique for Newton’s Method
• A nonmonotone trust region method for nonlinear programming with simple bound constraints
• A conic trust-region method for nonlinearly constrained optimization
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