A class of collinear scaling algorithms for bound-constrained optimization: Derivation and computational results

DOI10.1016/J.CAM.2008.11.005zbMath1169.65051OpenAlexW2017194577MaRDI QIDQ1026441

Wayne L. Tabor, Ariyawansa, K. A.

Publication date: 25 June 2009

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

Full work available at URL: https://doi.org/10.1016/j.cam.2008.11.005

zbMATH Keywords

algorithmconvergencenumerical resultsbarrier algorithmconic modelbarrier functionbound-constrained minimization problemouter and inner iterationsquadratic subproblems

Mathematics Subject Classification ID

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

Related Items (2)

A class of collinear scaling algorithms for bound-constrained optimization: convergence theorems ⋮ A CONIC AFFINE SCALING DOGLEG METHOD FOR NONLINEAR OPTIMIZATION WITH BOUND CONSTRAINTS

Uses Software

• CUTEr
• GQTPAR
• CUTE

Cites Work

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• Deriving collinear scaling algorithms as extensions of quasi-Newton methods and the local convergence of DFP- and BFGS-related collinear scaling algorithms
• A class of collinear scaling algorithms for bound-constrained optimization: convergence theorems
• Computing a Trust Region Step
• Conic Approximations and Collinear Scalings for Optimizers
• The Q-Superlinear Convergence of a Collinear Scaling Algorithm for Unconstrained Optimization
• Computing Optimal Locally Constrained Steps
• Newton’s Method with a Model Trust Region Modification
• On the Solution of Large Quadratic Programming Problems with Bound Constraints
• Numerical Optimization
• CUTE
• Trust Region Methods

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