Efficient time domain decomposition algorithms for parabolic PDE-constrained optimization problems

”Parareal” Time-Domain Decomposition for Time-dependent PDE-constrained Optimization

Domain Decomposition Methods for PDE Constrained Optimization Problems

Optimization problems constrained by nonlinear partial differential equations have been the focus of intense research in scientific computing lately. Current methods for the parallel numerical solution of such problems involve sequential quadratic programming (SQP), with either reduced or full space approaches. In this paper we propose and investigate a class of parallel full space SQP Lagrange...

Domain decomposition in time for PDE-constrained optimization

PDE-constrained optimization problems have a wide range of applications, but they lead to very large and ill-conditioned linear systems, especially if the problems are time dependent. In this paper we outline an approach for dealing with such problems by decomposing them in time and applying an additive Schwarz preconditioner in time, so that we can take advantage of parallel computers to deal ...

A Newton-picard Approach for Efficient Numerical Solution of Time-periodic Parabolic Pde Constrained Optimization Problems

We investigate an iterative method for the solution of time-periodic parabolic PDE constrained optimization problems. It is an inexact Sequential Quadratic Programming (iSQP) method based on the Newton-Picard approach. We present and analyze a linear quadratic model problem and prove optimal mesh-independent convergence rates. Additionally, we propose a two-grid variant of the Newton-Picard met...

Space-time Domain Decomposition for Parabolic Problems Space-time Domain Decomposition for Parabolic Problems

We analyze a space-time domain decomposition iteration, for a model advection diiusion equation in one and two dimensions. The asymptotic convergence rate is superlinear, and it is governed by the diiusion of the error across the overlap between subdomains. Hence, it depends on both the size of this overlap and the diiusion coeecient in the equation. However, it is independent of the number of ...