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9781611972047 Academic Inspection Copy

Computational Optimization of Systems Governed by Partial Differential Equations

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This book fills a gap between theory-oriented investigations in PDE-constrained optimization and the practical demands made by numerical solutions of PDE optimization problems. The authors discuss computational techniques representing recent developments that result from a combination of modern techniques for the numerical solution of PDEs and for sophisticated optimization schemes. Computational Optimization of Systems Governed by Partial Differential Equations offers readers a combined treatment of PDE-constrained optimization and uncertainties and an extensive discussion of multigrid optimization. It provides a bridge between continuous optimization and PDE modeling and focuses on the numerical solution of the corresponding problems.
Alfio Borzi is a Professor of Scientific Computing at the University of Wuerzburg, Germany. He has contributed considerably to the development of multigrid methodologies for simulation and optimization and to the modelling of quantum control problems. He has served as an associate editor of the SIAM Journal on Scientific Computing for many years and is a member of the editorial board of Numerical Mathematics: Theory, Methods and Applications. Volker Schulz is a Professor of Numerical Mathematics, Optimization Methods, and PDEs at the University of Trier. He has done research in shape optimization for aerodynamic problems in several collaborative projects between the German Aerospace Centre (DLR) and the aircraft industry. He is an initiating member of the special priority program Optimization with PDEs of the German Science Foundation and chairman of the GAMM (Gesellschaft fuer Angewandte Mathematik und Mechanik) special interest group on Optimization with PDEs. He is a member of the editorial boards of the SIAM Journal on Scientific Computing, Computing and Visualization in Science and Acta Applicandae Mathematicae.
Preface; 1. Introduction; 2. Optimality conditions; 3. Discretization of optimality systems; 4. Single-grid optimization; 5. Multigrid methods; 6. PDE optimization with uncertainty; 7. Applications; Bibliography; Index.
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