8076
2021
eng
A4095
A4120
6
43
article
0
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A primal dual projection algorithm for efficient constraint preconditioning
We consider a linear iterative solver for large scale linearly constrained quadratic minimization problems that arise, for example, in optimization with PDEs. By a primal-dual projection (PDP) iteration, which can be interpreted and analysed as a gradient method on a quotient space, the given problem can be solved by computing sulutions for a sequence of constrained surrogate problems, projections onto the feasible subspaces, and Lagrange multiplier updates. As a major application we consider a class of optimization problems with PDEs, where PDP can be applied together with a projected cg method using a block triangular constraint preconditioner. Numerical experiments show reliable and competitive performance for an optimal control problem in elasticity.
SIAM Journal on Scientific Computing
10.1137/20M1380739
yes
2021-08-18
Anton Schiela
Martin Weiser
Matthias StĂ¶cklein
Martin Weiser
Numerical Mathematics
Weiser, Martin
ZIB-Kaskade7
2020-SPP1962
Mathematics for Life and Materials Science
Modeling and Simulation of Complex Processes