TY - JOUR A1 - Schindele, Andreas A1 - Borzì, Alfio T1 - Proximal Methods for Elliptic Optimal Control Problems with Sparsity Cost Functional JF - Applied Mathematics N2 - First-order proximal methods that solve linear and bilinear elliptic optimal control problems with a sparsity cost functional are discussed. In particular, fast convergence of these methods is proved. For benchmarking purposes, inexact proximal schemes are compared to an inexact semismooth Newton method. Results of numerical experiments are presented to demonstrate the computational effectiveness of proximal schemes applied to infinite-dimensional elliptic optimal control problems and to validate the theoretical estimates. KW - semismooth Newton method KW - optimal control KW - elliptic PDE KW - nonsmooth optimization KW - proximal method Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-145850 VL - 7 IS - 9 ER - TY - INPR A1 - Breitenbach, Tim A1 - Borzì, Alfio T1 - On the SQH scheme to solve non-smooth PDE optimal control problems T2 - Numerical Functional Analysis and Optimization N2 - A sequential quadratic Hamiltonian (SQH) scheme for solving different classes of non-smooth and non-convex PDE optimal control problems is investigated considering seven different benchmark problems with increasing difficulty. These problems include linear and nonlinear PDEs with linear and bilinear control mechanisms, non-convex and discontinuous costs of the controls, L\(^1\) tracking terms, and the case of state constraints. The SQH method is based on the characterisation of optimality of PDE optimal control problems by the Pontryagin's maximum principle (PMP). For each problem, a theoretical discussion of the PMP optimality condition is given and results of numerical experiments are presented that demonstrate the large range of applicability of the SQH scheme. KW - SQH method KW - non-smooth optimization KW - Pontryagin maximum principle KW - nonconvex optimization Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-180936 N1 - This is an Accepted Manuscript of an article published by Taylor & Francis in Numerical Functional Analysis and Optimization on 27.04.2019, available online: http://www.tandfonline.com/10.1080/01630563.2019.1599911. ER - TY - JOUR A1 - Gaviraghi, Beatrice A1 - Schindele, Andreas A1 - Annunziato, Mario A1 - Borzì, Alfio T1 - On Optimal Sparse-Control Problems Governed by Jump-Diffusion Processes JF - Applied Mathematics N2 - A framework for the optimal sparse-control of the probability density function of a jump-diffusion process is presented. This framework is based on the partial integro-differential Fokker-Planck (FP) equation that governs the time evolution of the probability density function of this process. In the stochastic process and, correspondingly, in the FP model the control function enters as a time-dependent coefficient. The objectives of the control are to minimize a discrete-in-time, resp. continuous-in-time, tracking functionals and its L2- and L1-costs, where the latter is considered to promote control sparsity. An efficient proximal scheme for solving these optimal control problems is considered. Results of numerical experiments are presented to validate the theoretical results and the computational effectiveness of the proposed control framework. KW - jump-diffusion processes KW - partial integro-differential Fokker-Planck Equation KW - optimal control theory KW - nonsmooth optimization KW - proximal methods Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-147819 VL - 7 IS - 16 SP - 1978 EP - 2004 ER - TY - JOUR A1 - Bartsch, Jan A1 - Borzì, Alfio A1 - Fanelli, Francesco A1 - Roy, Souvik T1 - A numerical investigation of Brockett’s ensemble optimal control problems JF - Numerische Mathematik N2 - This paper is devoted to the numerical analysis of non-smooth ensemble optimal control problems governed by the Liouville (continuity) equation that have been originally proposed by R.W. Brockett with the purpose of determining an efficient and robust control strategy for dynamical systems. A numerical methodology for solving these problems is presented that is based on a non-smooth Lagrange optimization framework where the optimal controls are characterized as solutions to the related optimality systems. For this purpose, approximation and solution schemes are developed and analysed. Specifically, for the approximation of the Liouville model and its optimization adjoint, a combination of a Kurganov–Tadmor method, a Runge–Kutta scheme, and a Strang splitting method are discussed. The resulting optimality system is solved by a projected semi-smooth Krylov–Newton method. Results of numerical experiments are presented that successfully validate the proposed framework. KW - numerical analysis KW - Brockett KW - ensemble optimal control problems Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-265352 VL - 149 IS - 1 ER - TY - JOUR A1 - Breitenbach, Tim A1 - Borzì, Alfio T1 - The Pontryagin maximum principle for solving Fokker–Planck optimal control problems JF - Computational Optimization and Applications N2 - The characterization and numerical solution of two non-smooth optimal control problems governed by a Fokker–Planck (FP) equation are investigated in the framework of the Pontryagin maximum principle (PMP). The two FP control problems are related to the problem of determining open- and closed-loop controls for a stochastic process whose probability density function is modelled by the FP equation. In both cases, existence and PMP characterisation of optimal controls are proved, and PMP-based numerical optimization schemes are implemented that solve the PMP optimality conditions to determine the controls sought. Results of experiments are presented that successfully validate the proposed computational framework and allow to compare the two control strategies. KW - Fokker–Planck equation KW - Pontryagin maximum principle KW - non-smooth optimal control problems KW - stochastic processes Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-232665 SN - 0926-6003 VL - 76 ER - TY - JOUR A1 - Gathungu, Duncan Kioi A1 - Borzì, Alfio T1 - Multigrid Solution of an Elliptic Fredholm Partial Integro-Differential Equation with a Hilbert-Schmidt Integral Operator JF - Applied Mathematics N2 - An efficient multigrid finite-differences scheme for solving elliptic Fredholm partial integro-differential equations (PIDE) is discussed. This scheme combines a second-order accurate finite difference discretization of the PIDE problem with a multigrid scheme that includes a fast multilevel integration of the Fredholm operator allowing the fast solution of the PIDE problem. Theoretical estimates of second-order accuracy and results of local Fourier analysis of convergence of the proposed multigrid scheme are presented. Results of numerical experiments validate these estimates and demonstrate optimal computational complexity of the proposed framework. KW - elliptic problems KW - finite differences KW - fredholm operator KW - multigrid schemes KW - numerical analysis Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-158525 VL - 8 IS - 7 ER - TY - JOUR A1 - Kienle-Garrido, Melina-Lorén A1 - Breitenbach, Tim A1 - Chudej, Kurt A1 - Borzì, Alfio T1 - Modeling and numerical solution of a cancer therapy optimal control problem JF - Applied Mathematics N2 - A mathematical optimal-control tumor therapy framework consisting of radio- and anti-angiogenesis control strategies that are included in a tumor growth model is investigated. The governing system, resulting from the combination of two well established models, represents the differential constraint of a non-smooth optimal control problem that aims at reducing the volume of the tumor while keeping the radio- and anti-angiogenesis chemical dosage to a minimum. Existence of optimal solutions is proved and necessary conditions are formulated in terms of the Pontryagin maximum principle. Based on this principle, a so-called sequential quadratic Hamiltonian (SQH) method is discussed and benchmarked with an “interior point optimizer―a mathematical programming language” (IPOPT-AMPL) algorithm. Results of numerical experiments are presented that successfully validate the SQH solution scheme. Further, it is shown how to choose the optimisation weights in order to obtain treatment functions that successfully reduce the tumor volume to zero. KW - cancer KW - therapy KW - optimal control problem Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-177152 VL - 9 IS - 8 ER - TY - JOUR A1 - Campana, Francesca Calà A1 - Borzì, Alfio T1 - On the SQH Method for Solving Differential Nash Games JF - Journal of Dynamical and Control Systems N2 - A sequentialquadratic Hamiltonian schemefor solving open-loop differential Nash games is proposed and investigated. This method is formulated in the framework of the Pontryagin maximum principle and represents an efficient and robust extension of the successive approximations strategy for solving optimal control problems. Theoretical results are presented that prove the well-posedness of the proposed scheme, and results of numerical experiments are reported that successfully validate its computational performance. KW - successive approximations strategy KW - sequential quadratic hamiltonian method KW - differential nash games KW - pontryagin maximum principle Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-269111 SN - 1573-8698 VL - 28 ER -