An Efficient Primal-Dual Method for the Obstacle Problem
Dominique Zosso, Braxton Osting, Mandy Xia, Stanley J. Osher
Journal of Scientific Computing
We solve the non-linearized and linearized obstacle problems efficiently using a primal-dual hybrid gradients method involving projection and/or L^1 penalty. Since this method requires no matrix inversions or explicit identification of the contact set, we find that this method, on a variety of test problems, achieves the precision of previous methods with a speed up of 1–2 orders of magnitude. The derivation of this method is disciplined, relying on a saddle point formulation of the convex problem, and can be adapted to a wide range of other constrained convex optimization problems.
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