Donald Samuels, Ian Stobert
SPIE Photomask Technology + EUV Lithography 2007
Many industrial problems can be naturally formulated using mixed integer non-linear programming (MINLP) models and can be solved by spatial BranchBound (sBB) techniques. We study the impact of two important parts of sBB methods: bounds tightening (BT) and branching strategies. We extend a branching technique originally developed for MILP, reliability branching, to the MINLP case. Motivated by the demand for open-source solvers for real-world MINLP problems, we have developed an sBB software package named couenne (Convex Over- and Under-ENvelopes for Non-linear Estimation) and used it for extensive tests on several combinations of BT and branching techniques on a set of publicly available and real-world MINLP instances. We also compare the performance of couenne with a state-of-the-art MINLP solver. © 2009 Taylor & Francis.
Donald Samuels, Ian Stobert
SPIE Photomask Technology + EUV Lithography 2007
R.A. Brualdi, A.J. Hoffman
Linear Algebra and Its Applications
Jaione Tirapu Azpiroz, Alan E. Rosenbluth, et al.
SPIE Photomask Technology + EUV Lithography 2009
John R. Kender, Rick Kjeldsen
IEEE Transactions on Pattern Analysis and Machine Intelligence