Structured spectral algorithm with a nonmonotone line search for nonlinear least squares

DOI10.1016/j.apnum.2022.10.008OpenAlexW4307046903MaRDI QIDQ2106221

Hassan Mohammad, Kamaluddeen Umar Danmalam

Publication date: 9 December 2022

Published in: Applied Numerical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apnum.2022.10.008

zbMATH Keywords

global convergencenumerical experimentsspectral parameternonmonotone line searchnonlinear least squares problems

Mathematics Subject Classification ID

Quadratic programming (90C20)

Uses Software

• minpack

Cites Work

• A literature survey of benchmark functions for global optimisation problems
• Recent advances in numerical methods for nonlinear equations and nonlinear least squares
• Nonlinear conjugate gradient methods with structured secant condition for nonlinear least squares problems
• A structured diagonal Hessian approximation method with evaluation complexity analysis for nonlinear least squares
• Structured diagonal Gauss-Newton method for nonlinear least squares
• A brief survey of methods for solving nonlinear least-squares problems
• A family of spectral gradient methods for optimization
• Scaled nonlinear conjugate gradient methods for nonlinear least squares problems
• Structured two-point stepsize gradient methods for nonlinear least squares
• The Barzilai and Borwein Gradient Method for the Large Scale Unconstrained Minimization Problem
• Two-Point Step Size Gradient Methods
• Testing Unconstrained Optimization Software
• On the Use of Product Structure in Secant Methods for Nonlinear Least Squares Problems
• A Nonmonotone Line Search Technique and Its Application to Unconstrained Optimization
• A derivative-free nonmonotone line search and its application to the spectral residual method
• Spectral residual method without gradient information for solving large-scale nonlinear systems of equations
• Gobally convergent variable metric method for nonconvex nondifferentiable unconstrained minimization
• Benchmarking optimization software with performance profiles.

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