Extended Linear-quadratic Programming

@inproceedings{RockafellarExtendedLP,
  title={Extended Linear-quadratic Programming},
  author={Terry Rockafellar}
}
  • Terry Rockafellar
Most work in numerical optimization starts from the convention that the problem to be solved is given in the form (P) minimize f 0 (x) over all x ∈ X, with X ⊂ lR n. But this notion of what optimization is all about may be unnecessarily limiting, both in the kind of modeling it promotes and the computational approaches it suggests. While all optimization eventually boils down to minimizing some function over some set, the formulation (P) says nothing about the mathematical structure of the… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-9 of 9 references

Computational schemes for solving large-scale problems in extended linear-quadratic programming

R T Rockafellar
Math. Prog., Ser. B • 1990

Linear-quadratic problems with stochastic penalties: the finite generation algorithm, in: Numerical Techniques for Stochastic Optimization

R T Rockafellar, R J Wets
Lecture Notes in Control and Information Sciences • 1987

Linear-quadratic programming and optimal control

R T Rockafellar
SIAM J. Control Opt • 1987

A Lagrangian finite generation technique for solving linear-quadratic problems in stochastic programming

R T Rockafellar, R J Wets
Math. Prog. Studies • 1986

Forward-backward splitting methods in Lagrangian optimization

H G Chen, R T Rockafellar
SIAM J. Optimization

Similar Papers

Loading similar papers…