A New Diagonal Quasi-Newton Updating Method With Scaled Forward Finite Differences Directional Derivative for Unconstrained Optimization

DOI10.1080/01630563.2018.1552293zbMath1417.49037OpenAlexW2945911381WikidataQ127835652 ScholiaQ127835652MaRDI QIDQ5384612

Neculai Andrei

Publication date: 24 June 2019

Published in: Numerical Functional Analysis and Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01630563.2018.1552293

zbMATH Keywords

unconstrained optimizationglobal convergencenumerical comparisonsdirectional derivativesdiagonal quasi-Newton updating

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Newton-type methods (49M15)

Related Items

A new accelerated diagonal quasi-Newton updating method with scaled forward finite differences directional derivative for unconstrained optimization, Diagonal BFGS updates and applications to the limited memory BFGS method

Uses Software

• L-BFGS
• CUTEr
• MINPACK-2
• KELLEY
• tn
• CUTE

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