arXiv:1912.09232
Improving Clique Decompositions of Semidefinite Relaxations for Optimal Power Flow Problems
Improving Clique Decompositions of Semidefinite Relaxations for Optimal Power Flow Problems
著者: Julie Sliwak, Miguel Anjos, Lucas Létocart, Jean Maeght, Emiliano Traversi
分類: math.OC, cs.RO
原文アブストラクト
Semidefinite Programming (SDP) provides tight lower bounds for Optimal Power Flow problems. However, solving large-scale SDP problems requires exploiting sparsity. In this paper, we experiment several clique decomposition algorithms that lead to different reformulations and we show that the resolution is highly sensitive to the clique decomposition procedure. Our main contribution is to demonstrate that minimizing the number of additional edges in the chordal extension is not always appropriate to get a good clique decomposition.