1 Interior-point methods for large-scale cone programming

@inproceedings{Andersen20101IM,
  title={1 Interior-point methods for large-scale cone programming},
  author={Martin Andersen},
  year={2010}
}
In the conic formulation of a convex optimization problem the constraints are expressed as linear inequalities with respect to a possibly non-polyhedral convex cone. This makes it possible to formulate elegant extensions of interior-point methods for linear programming to general nonlinear convex optimization. Recent research on cone programming algorithms has particularly focused on three convex cones, for which symmetric primal-dual methods have been developed: the nonnegative orthant, the… CONTINUE READING
Highly Cited
This paper has 45 citations. REVIEW CITATIONS
29 Citations
34 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 29 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 34 references

Interior-point polynomial methods in convex programming, volume 13 of Studies in Applied Mathematics

  • Yu. Nesterov, A. Nemirovskii
  • 1994
Highly Influential
4 Excerpts

Similar Papers

Loading similar papers…