An Efficient Primal-Dual Method for the Obstacle Problem

作者：Zosso Dominique^*; Osting Braxton; Xia Mandy; Osher Stanley J

来源：Journal of Scientific Computing, 2017, 73(1): 416-437.

DOI：10.1007/s10915-017-0420-0

• Obstacle problem
• Minimal surface
• Convex optimization
• Primal-dual hybrid gradients

We solve the non-linearized and linearized obstacle problems efficiently using a primal-dual hybrid gradients method involving projection and/or 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.

• 出版日期2017-10