SIAM Journal on Scientific and Statistical Computing - Special issue on iterative methods in numerical linear algebra
Iterative solution methods
A Scalable Substructuring Method by Lagrange Multipliers for Plate Bending Problems
SIAM Journal on Numerical Analysis
Duality-based domain decomposition with natural coarse-space for variational inequalities0
Journal of Computational and Applied Mathematics
A Numerical Study of FETI Algorithms for Mortar Finite Element Methods
SIAM Journal on Scientific Computing
Dual-Primal FETI Methods for Three-Dimensional Elliptic Problems with Heterogeneous Coefficients
SIAM Journal on Numerical Analysis
Box Constrained Quadratic Programming with Proportioning and Projections
SIAM Journal on Optimization
Journal of Computational and Applied Mathematics - Special issue: Proceedings of the 9th International Congress on computational and applied mathematics
FETI and FETI-DP Methods for Spectral and Mortar Spectral Elements: A Performance Comparison
Journal of Scientific Computing
Scalability and FETI based algorithm for large discretized variational inequalities
Mathematics and Computers in Simulation - MODELLING 2001 - Second IMACS conference on mathematical modelling and computational methods in mechanics, physics, biomechanics and geodynamics
Monotone Multigrid Methods on Nonmatching Grids for Nonlinear Multibody Contact Problems
SIAM Journal on Scientific Computing
A scalable FETI-DP algorithm with non-penetration mortar conditions on contact interface
Journal of Computational and Applied Mathematics
Computational Optimization and Applications
Mathematics and Computers in Simulation
Hi-index | 0.00 |
We develop an optimal algorithm for the numerical solution of coercive variational inequalities, by combining FETI algorithms of dual-primal type with recent results for bound constrained quadratic programming problems. The discretized version of the model problem, obtained by using the FETI-DP methodology, is reduced by the duality theory of convex optimization to a quadratic programming problem with bound constraints. The resulting problem is solved by a new algorithm with a known rate of convergence given in terms of the spectral condition number of the quadratic problem. We present convergence bounds that guarantee the scalability of the algorithm. These results are confirmed by numerical experiments.