A super-linear convergent gradient projection type algorithm for linearly constrained problems

DOI10.1016/0377-2217(84)90288-1zbMath0557.90076OpenAlexW2079733897MaRDI QIDQ761975

D. Kharzeev

Publication date: 1984

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0377-2217(84)90288-1

zbMATH Keywords

linear constraintssuperlinear convergencevariable metric methodgradient projectionconvex objective functions

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Convex programming (90C25) Methods of successive quadratic programming type (90C55)

Related Items (5)

A new generalized gradient projection type algorithm for linearly constrained problems ⋮ A class of trust region methods for linear inequality constrained optimization and its theory analysis. I: Algorithm and global convergence ⋮ A class of trust region methods for linear inequality constrained optimization and its theory analysis. II: Local convergence rate and numerical tests ⋮ A generalized gradient projection method for optimization problems with equality and inequality constraints about arbitrary initial point ⋮ A robust superlinearly convergent algorithm for linearly constrained optimization problems under degeneracy

Cites Work

• On the Convergence of the Variable Metric Algorithm
• On the Convergence of Gradient Methods under Constraint
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: A super-linear convergent gradient projection type algorithm for linearly constrained problems