An adaptive nonmonotone trust region method based on a modified scalar approximation of the Hessian in the successive quadratic subproblems

DOI10.1051/ro/2017057zbMath1461.65182OpenAlexW2739392069MaRDI QIDQ5242267

Saman Babaie-Kafaki, Saeed Rezaee

Publication date: 6 November 2019

Published in: RAIRO - Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1051/ro/2017057

zbMATH Keywords

unconstrained optimizationglobal convergencesuperlinear convergencetrust region methodadaptive radiussecant equation

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Methods of quasi-Newton type (90C53) Numerical methods based on nonlinear programming (49M37)

Related Items (1)

Improved high-dimensional regression models with matrix approximations applied to the comparative case studies with support vector machines

Uses Software

• CUTEr
• CG_DESCENT
• SCALCG

Cites Work

• Adaptive cubic regularisation methods for unconstrained optimization. I: Motivation, convergence and numerical results
• A nonmonotone trust region method with adaptive radius for unconstrained optimization problems
• A self-adaptive trust region method with line search based on a simple subproblem model
• On optimality of the parameters of self-scaling memoryless quasi-Newton updating formulae
• Accelerating the cubic regularization of Newton's method on convex problems
• A nonmonotone trust region method based on simple quadratic models
• Accelerated scaled memoryless BFGS preconditioned conjugate gradient algorithm for unconstrained optimization
• A modified scaled memoryless BFGS preconditioned conjugate gradient method for unconstrained optimization
• Cubic regularization of Newton method and its global performance
• Optimization theory and methods. Nonlinear programming
• An adaptive trust region method and its convergence
• A new nonmonotone adaptive trust region method based on simple quadratic models
• On the Global Convergence of the BFGS Method for Nonconvex Unconstrained Optimization Problems
• An adaptive nonmonotone trust region method for unconstrained optimization problems based on a simple subproblem
• A nonlinear conjugate gradient method based on the MBFGS secant condition
• Algorithm 851
• Two-Point Step Size Gradient Methods
• Self-Scaling Variable Metric (SSVM) Algorithms
• Optimal conditioning of self-scaling variable Metric algorithms
• The Quasi-Cauchy Relation and Diagonal Updating
• An Assessment of Nonmonotone Linesearch Techniques for Unconstrained Optimization
• CUTEr and SifDec
• A modified BFGS method and its global convergence in nonconvex minimization
• Benchmarking optimization software with performance profiles.

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