Globally Convergent Primal-Dual Active-Set Methods with Inexact Subproblem Solves

@article{Curtis2016GloballyCP,
  title={Globally Convergent Primal-Dual Active-Set Methods with Inexact Subproblem Solves},
  author={Frank E. Curtis and Zheng Han},
  journal={SIAM J. Optim.},
  year={2016},
  volume={26},
  pages={2261-2283}
}
We propose primal-dual active-set (PDAS) methods for solving large-scale instances of an important class of convex quadratic optimization problems (QPs). The iterates of the algorithms are partitions of the index set of variables, where corresponding to each partition there exist unique primal-dual variables that can be obtained by solving a (reduced) linear system. Algorithms of this type have recently received attention when solving certain QPs and linear complementarity problems since, with… 

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