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Computational Optimization of Systems Governed by Partial Differential Equations

Computational Optimization of Systems Governed by Partial Differential Equations

Computational Optimization of Systems Governed by Partial Differential Equations

Alfio Borzì, Julius-Maximilians-Universität Würzburg, Germany
Volker Schulz, Universität Trier, Germany
January 2012
Paperback
9781611972047
NZD$200.00
inc GST
Paperback

    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 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 modelling and focuses on the numerical solution of the corresponding problems. Intended for graduate students in PDE-constrained optimization, it is also suitable as an introduction for researchers in scientific computing or optimization. It will also help researchers in the natural sciences and engineering to formulate and solve optimization problems.

    • Includes an extensive discussion of multigrid optimization
    • Covers recent developments in the subject
    • Suitable for use as a graduate textbook

    Product details

    January 2012
    Paperback
    9781611972047
    306 pages
    255 × 178 × 15 mm
    0.54kg
    This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.

    Table of Contents

    • 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.