A smoothing Newton method for a type of inverse semi-definite quadratic programming problem

DOI10.1016/j.cam.2008.01.028zbMath1155.65051OpenAlexW1982636073MaRDI QIDQ953410

Xiantao Xiao, Li-wei Zhang, Zhang, Jianzhong

Publication date: 20 November 2008

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2008.01.028

zbMATH Keywords

global convergencenumerical resultsquadratic convergencesmoothing Newton methodinverse optimizationsemi-definite quadratic programming

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Semidefinite programming (90C22) Quadratic programming (90C20)

Related Items

An interior-point algorithm for solving inverse linear optimization problem, A wide neighborhood interior-point algorithm for convex quadratic semidefinite optimization, A majorized penalty approach to inverse linear second order cone programming problems, On linear programs with linear complementarity constraints, The augmented Lagrangian method for a type of inverse quadratic programming problems over second-order cones, Unnamed Item, Primal-dual interior-point algorithm for convex quadratic semi-definite optimization, A nonconvex ADMM for a class of sparse inverse semidefinite quadratic programming problems, Inverse semidefinite quadratic programming problem with \(l_1\) norm measure, Inverse quadratic programming problem with \(l_1\) norm measure, An alternating direction method for solving a class of inverse semi-definite quadratic programming problems, A perturbation approach for an inverse quadratic programming problem over second-order cones

Uses Software

• Matlab
• CGS

Cites Work

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