QSDPNAL: a two-phase augmented Lagrangian method for convex quadratic semidefinite programming

@article{Li2018QSDPNALAT,
  title={QSDPNAL: a two-phase augmented Lagrangian method for convex quadratic semidefinite programming},
  author={Xudong Li and Defeng Sun and Kim-Chuan Toh},
  journal={Math. Program. Comput.},
  year={2018},
  volume={10},
  pages={703-743}
}
In this paper, we present a two-phase augmented Lagrangianmethod, called QSDPNAL, for solving convex quadratic semidefinite programming (QSDP) problems with constraints consisting of a large number of linear equality and inequality constraints, a simple convex polyhedral set constraint, and a positive semidefinite cone constraint. A first order algorithm which relies on the inexact Schur complement based decomposition technique is developed in QSDPNAL-Phase I with the aim of solving a QSDP… CONTINUE READING

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