Strengthening Convex Relaxations with Bound Tightening for Power Network Optimization

@inproceedings{Coffrin2015StrengtheningCR,
  title={Strengthening Convex Relaxations with Bound Tightening for Power Network Optimization},
  author={Carleton Coffrin and Hassan L. Hijazi and Pascal Van Hentenryck},
  booktitle={CP},
  year={2015}
}
Convexification is a fundamental technique in (mixed-integer) nonlinear optimization and many convex relaxations are parametrized by variable bounds, i.e., the tighter the bounds, the stronger the relaxations. This paper studies how bound tightening can improve convex relaxations for power network optimization. It adapts traditional constraintprogramming concepts (e.g., minimal network and bound consistency) to a relaxation framework and shows how bound tightening can dramatically improve power… CONTINUE READING
Highly Cited
This paper has 29 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 22 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 42 references

Semidefinite programming for optimal power flow problems

  • X. Bai, H. Wei, K. Fujisawa, Y. Wang
  • International Journal of Electrical Power…
  • 2008
Highly Influential
8 Excerpts

Convex quadratic relaxations of mixedinteger nonlinear programs in power systems

  • H. Hijazi, C. Coffrin, P. Van Hentenryck
  • Published online at http://www. optimization…
  • 2013
Highly Influential
5 Excerpts

AMPL: A Mathematical Programming Language

  • R. Fourer, D. M. Gay, B. Kernighan
  • Wallace, S.W. (ed.) Algorithms and Model…
  • 1989
Highly Influential
2 Excerpts

Similar Papers

Loading similar papers…