The computational solution of problems can be restricted by the availability of solution
methods for linear (ized) systems of equations. In conjunction with iterative methods …

This article addresses the inference of physics models from data, from the perspectives of
inverse problems and model reduction. These fields develop formulations that integrate data …

This is a book on Optimal Control Problems (OCPs): how to formulate them, how to set up a
suitable mathematical framework for their analysis, how to approximate them numerically …

This work proposes a space--time least-squares Petrov--Galerkin (ST-LSPG) projection
method for model reduction of nonlinear dynamical systems. In contrast to typical nonlinear …

In this article, we motivate, derive, and test effective preconditioners to be used with the
Minres algorithm for solving a number of saddle point systems which arise in PDE …

Saddle point matrices of a special structure arise in optimal control problems. In this paper
we consider distributed optimal control for various types of scalar stationary partial …

Although design optimization has shown its great power of automatizing the whole design
process and providing an optimal design, using sophisticated computational models, its …

In this paper we investigate the possibility of using a block‐triangular preconditioner for
saddle point problems arising in PDE‐constrained optimization. In particular, we focus on a …

The solution of time-dependent PDE-constrained optimization problems subject to unsteady
flow equations presents a challenge to both algorithms and computing power. In this paper …

Sometimes, in a tournament competition to form a single team from two teams, 50% players
are selected from the union of both teams according to their performance (fitness) …