Uniform boundedness of the inverse of a Jacobian matrix arising in regularized interior-point methods

DOI10.1007/s10107-011-0498-3zbMath1260.49058OpenAlexW2069159962MaRDI QIDQ1942268

Joël Benoist, Paul Armand

Publication date: 18 March 2013

Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10107-011-0498-3

zbMATH Keywords

constrained optimizationprimal-dual interior-point method

Mathematics Subject Classification ID

Ill-posedness and regularization problems in numerical linear algebra (65F22) Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Linear programming (90C05) Numerical methods based on nonlinear programming (49M37) Interior-point methods (90C51) Direct numerical methods for linear systems and matrix inversion (65F05)

Related Items

A regularized interior-point method for constrained linear least squares, A mixed logarithmic barrier-augmented Lagrangian method for nonlinear optimization, Dynamic non-diagonal regularization in interior point methods for linear and convex quadratic programming, Proximal stabilized interior point methods and \textit{low-frequency-update} preconditioning techniques, A primal-dual regularized interior-point method for convex quadratic programs, An interior point-proximal method of multipliers for convex quadratic programming, Rapid infeasibility detection in a mixed logarithmic barrier-augmented Lagrangian method for nonlinear optimization, Local convergence analysis of a primal-dual method for bound-constrained optimization without SOSC, An interior point-proximal method of multipliers for linear positive semi-definite programming, Boundedness of the inverse of a regularized Jacobian matrix in constrained optimization and applications

Uses Software

• Ipopt

Cites Work

• Unnamed Item
• A primal-dual regularized interior-point method for convex quadratic programs
• On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming
• Interior-point \(\ell_2\)-penalty methods for nonlinear programming with strong global convergence properties
• From global to local convergence of interior methods for nonlinear optimization