Preconditioners for state constrained optimal control problems with Moreau-Yosida penalty function

Optimal control problems with partial differential equations as constraints play an important role in many applications. The inclusion of bound constraints for the state variable poses a significant challenge for optimization methods. Our focus here is on the incorporation of the constraints via the Moreau-Yosida regularization technique. This method has been studied recently and has proven to be advantageous compared to other approaches. In this paper we develop robust preconditioners for the efficient solution of the Newton steps associated with solving the Moreau-Yosida regularized problem. Numerical results illustrate the efficiency of our approach

Parallel Unsmoothed Aggregation Algebraic Multigrid Algorithms on GPUs

We design and implement a parallel algebraic multigrid method for isotropic graph Laplacian problems on multicore Graphical Processing Units (GPUs). The proposed AMG method is based on the aggregation framework. The setup phase of the algorithm uses a parallel maximal independent set algorithm in forming aggregates and the resulting coarse level hierarchy is then used in a K-cycle iteration solve phase with a $\ell^1$-Jacobi smoother. Numerical tests of a parallel implementation of the method for graphics processors are presented to demonstrate its effectiveness.Comment: 18 pages, 3 figure

Nonparametric frontier estimation from noisy data

A new nonparametric estimator of production frontiers is defined and studied when the data set of production units is contaminated by measurement error. The measurement error is assumed to be an additive normal random variable on the input variable, but its variance is unknown. The estimator is a modification of the m-frontier, which necessitates the computation of a consistent estimator of the conditional survival function of the input variable given the output variable. In this paper, the identification and the consistency of a new estimator of the survival function is proved in the presence of additive noise with unknown variance. The performance of the estimator is also studied through simulated data.production frontier, deconvolution, measurement error, efficiency analysis

Multilevel Schwarz Methods for Porous Media Problems

In this thesis, efficient overlapping multilevel Schwarz preconditioners are used to iteratively solve Hdiv-conforming finite element discretizations of models in poroelasticity, and an innovative two-scale multilevel Schwarz method is developed for the solution of pore-scale porous media models. The convergence of two-level Schwarz methods is rigorously proven for Biot’s consolidation model, as well as a Biot-Brinkman model by utilizing the conservation property of the discretization. The numerical performance of the proposed multiplicative and hybrid two-level Schwarz methods is tested in different problem settings by covering broad ranges of the parameter regimes, showing robust results in variations of the parameters in the system that are uniform in the mesh size. For extreme parameters a scaling of the system yields robustness of the iteration counts. Optimality of the relaxation factor of the hybrid method is investigated and the performance of the multilevel methods is shown to be nearly identical to the two-level case. The additional diffusion term in the Biot-Brinkman model yields a stabilization for high permeabilities. Additionally, a homogenizing two-scale multilevel Schwarz preconditioner is developed for the iterative solution of high-resolution computations of flow in porous media at the pore scale, i.e., a Stokes problem in a periodically perforated domain. Different homogenized operators known from the literature are used as coarse-scale operators within a multilevel Schwarz preconditioner applied to Hdiv-conforming discretizations of an extended model problem. A comparison in the numerical performance tests shows that an operator of Brinkman type with optimized effective tensor yields the best performance results in an axisymmetric configuration and a moderately anisotropic geometry of the obstacles, outperforming Darcy and Stokes as coarse-scale operators, as well as a standard multigrid method, that serves as a benchmark test