Stable iterative Lagrange principle in convex programming as a tool for solving unstable problems

DOI10.1134/S0965542517010092zbMath1373.90156MaRDI QIDQ2357119

M. I. Sumin, F. A. Kuterin

Publication date: 19 June 2017

Published in: Computational Mathematics and Mathematical Physics (Search for Journal in Brave)

zbMATH Keywords

convex optimizationHilbert spacesiterative regularizationperturbed optimization problems

Mathematics Subject Classification ID

Convex programming (90C25) Optimality conditions and duality in mathematical programming (90C46) Sensitivity, stability, parametric optimization (90C31) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20)

Related Items (2)

On the regularization of the Lagrange principle and on the construction of the generalized minimizing sequences in convex constrained optimization problems ⋮ On the regularization of classical optimality conditions in a convex optimal control problem with state constraints

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Suboptimal control of distributed-parameter systems: Minimizing sequences and the value function
• Suboptimal control of distributed parameter systems: Normality properties and dual subgradient method
• Regularized parametric Kuhn-Tucker theorem in a Hilbert space
• Stable sequential convex programming in a Hilbert space and its application for solving unstable problems
• Methods for solving monotonic variational inequalities, based on the principle of iterative regularization
• Duality-based regularization in a linear convex mathematical programming problem

This page was built for publication: Stable iterative Lagrange principle in convex programming as a tool for solving unstable problems