A retrospective trust-region method for unconstrained optimization

DOI10.1007/s10107-008-0258-1zbMath1196.65101OpenAlexW2130895332WikidataQ58185780 ScholiaQ58185780MaRDI QIDQ964178

Mélodie Mouffe, Dimitri Tomanos, Fabian Bastin, Vincent Malmedy, Phillipe L. Toint

Publication date: 15 April 2010

Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10107-008-0258-1

zbMATH Keywords

algorithmunconstrained optimizationconvergencenumerical experimentstrust region methodsnoisy functions

Mathematics Subject Classification ID

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

Related Items (8)

A hybrid of adjustable trust-region and nonmonotone algorithms for unconstrained optimization ⋮ A new nonmonotone adaptive retrospective trust region method for unconstrained optimization problems ⋮ Unnamed Item ⋮ A trust-region method for unconstrained multiobjective problems with applications in satisficing processes ⋮ Nonlinear stepsize control, trust regions and regularizations for unconstrained optimization ⋮ An effective trust-region-based approach for symmetric nonlinear systems ⋮ Adaptive trust-region algorithms for unconstrained optimization ⋮ Recent advances in trust region algorithms

Uses Software

• CUTEr
• SifDec
• AMLET
• GQTPAR

Cites Work

• Unnamed Item
• An adaptive Monte Carlo algorithm for computing mixed logit estimators
• Computing a Trust Region Step
• The Conjugate Gradient Method and Trust Regions in Large Scale Optimization
• Trust Region Methods
• Analysis of Sample-Path Optimization
• CUTEr and SifDec
• Benchmarking optimization software with performance profiles.

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