A More Lenient Stopping Rule for Line Search Algorithms

DOI10.1080/1055678021000049363zbMath1040.90039OpenAlexW2097281366MaRDI QIDQ4709751

Tamar Schlick, Dexuan Xie

Publication date: 2002

Published in: Optimization Methods and Software (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/1055678021000049363

zbMATH Keywords

descent methodline searchtruncated Newton methodmolecular potential minimization

Mathematics Subject Classification ID

Nonlinear programming (90C30) Approximation methods and heuristics in mathematical programming (90C59) Numerical methods based on nonlinear programming (49M37) Molecular structure (graph-theoretic methods, methods of differential topology, etc.) (92E10)

Related Items (1)

Convergence analysis of truncated incomplete Hessian Newton minimization method and application in biomolecular potential energy minimization

Uses Software

• TNPACK

Cites Work

• Unnamed Item
• Unnamed Item
• Truncated-Newton algorithms for large-scale unconstrained optimization
• Testing Unconstrained Optimization Software
• Line search algorithms with guaranteed sufficient decrease
• Remark on Algorithm 566
• TNPACK—A truncated Newton minimization package for large-scale problems
• TNPACK—a truncated Newton minimization package for large-scale problems
• Remark on Algorithm 702—the updated truncated Newton minimization package
• Efficient Implementation of the Truncated-Newton Algorithm for Large-Scale Chemistry Applications
• Minimization Algorithms Making Use of Non-quadratic Properties of the Objective Function

This page was built for publication: A More Lenient Stopping Rule for Line Search Algorithms