A new accelerated diagonal quasi-Newton updating method with scaled forward finite differences directional derivative for unconstrained optimization
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Publication:5151541
DOI10.1080/02331934.2020.1712391zbMath1460.90204OpenAlexW2999927963MaRDI QIDQ5151541
Publication date: 19 February 2021
Published in: Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02331934.2020.1712391
unconstrained optimizationglobal convergencenumerical comparisonsdirectional derivativesdiagonal quasi-Newton updating
Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Methods of quasi-Newton type (90C53)
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- Scaling on diagonal quasi-Newton update for large-scale unconstrained optimization
- On optimality of the parameters of self-scaling memoryless quasi-Newton updating formulae
- Some numerical experiments with variable-storage quasi-Newton algorithms
- Numerical expirience with a class of self-scaling quasi-Newton algorithms
- Continuous nonlinear optimization for engineering applications in GAMS technology
- A diagonal quasi-Newton updating method for unconstrained optimization
- Optimization theory and methods. Nonlinear programming
- An acceleration of gradient descent algorithm with backtracking for unconstrained opti\-mi\-za\-tion
- Sizing and Least-Change Secant Methods
- A Tool for the Analysis of Quasi-Newton Methods with Application to Unconstrained Minimization
- Self-Scaling Variable Metric (SSVM) Algorithms
- Optimal conditioning of self-scaling variable Metric algorithms
- Quasi-Newton Methods, Motivation and Theory
- Conjugate Gradient Methods with Inexact Searches
- CUTE
- A diagonal quasi-Newton updating method based on minimizing the measure function of Byrd and Nocedal for unconstrained optimization
- The Quasi-Cauchy Relation and Diagonal Updating
- A Characterization of Superlinear Convergence and Its Application to Quasi-Newton Methods
- A New Diagonal Quasi-Newton Updating Method With Scaled Forward Finite Differences Directional Derivative for Unconstrained Optimization
- Convergence Conditions for Ascent Methods
- Convergence Conditions for Ascent Methods. II: Some Corrections
- Benchmarking optimization software with performance profiles.