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Large-Scale Optimization with Applications

Part I: Optimization in Inverse Problems and Design

  • Book
  • © 1997

Overview

Editors:
  1. Lorenz T. Biegler

    1. Chemical Engineering Department, Carnegie Mellon University, Pittsburgh, USA

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  2. Thomas F. Coleman

    1. Computer Science Department, Cornell University, Ithaca, USA

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  3. Andrew R. Conn

    1. Thomas J. Watson Research Center, Yorktown Heights, USA

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  4. Fadil N. Santosa

    1. School of Mathematics, University of Minnesota, Minneapolis, USA

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Part of the book series: The IMA Volumes in Mathematics and its Applications (IMA, volume 92)

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Table of contents (11 chapters)

  1. Front Matter

    Pages i-xv
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  2. Space Mapping Optimization for Engineering Design

    • John W. Bandler, Radek M. Biernacki, Shaohua Chen, Ronald H. Hemmers, Kaj Madsen
    Pages 1-15

  3. An Inverse Problem in Plasma Physics: the Identification of the Current Density Profile in a Tokamak

    • J. Blum, H. Buvat
    Pages 17-36

  4. Duality for Inverse Problems in Wave Propagation

    • Mark S. Gockenbach, William W. Symes
    Pages 37-61

  5. Piecewise Differentiable Minimization for Ill-Posed Inverse Problems

    • Yuying Li
    Pages 63-79

  6. The Use of Optimization in the Reconstruction of Obstacles from Acoustic or Electromagnetic Scattering Data

    • Pierluigi Maponi, Maria Cristina Recchioni, Francesco Zirilli
    Pages 81-100

  7. Design of 3D-Reflectors for Near Field and Far Field Problems

    • Andreas Neubauer
    Pages 101-118

  8. Optimal Die Shape and Ram Velocity Design for Metal Forging

    • Linda D. Smith, Jordan M. Berg, James C. Malas III
    Pages 119-133

  9. Eigenvalues in Optimum Structural Design

    • Ulf Torbjörn Ringertz
    Pages 135-149

  10. Optimization Issues in Ocean Acoustics

    • A. Tolstoy
    Pages 151-172

  11. Gradient Methods in Inverse Acoustic and Electromagnetic Scattering

    • P. M. Van Den Berg, R. E. Kleinman
    Pages 173-194

  12. Atmospheric Data Assimilation Based on the Reduced Hessian Successive Quadratic Programming Algorithm

    • Y. F. Xie
    Pages 195-204

  13. Back Matter

    Pages 205-210
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Keywords

About this book

Inverse problems and optimal design have come of age as a consequence of the availability of better, more accurate, and more efficient simulation packages. Many of these simulators, which can run on small workstations, can capture the complicated behavior of the physical systems they are modeling, and have become commonplace tools in engineering and science. There is a great desire to use them as part of a process by which measured field data are analyzed or by which design of a product is automated. A major obstacle in doing precisely this is that one is ultimately confronted with a large-scale optimization problem. This volume contains expository articles on both inverse problems and design problems formulated as optimization. Each paper describes the physical problem in some detail and is meant to be accessible to researchers in optimization as well as those who work in applied areas where optimization is a key tool. What emerges in the presentations is that there are features about the problem that must be taken into account in posing the objective function, and in choosing an optimization strategy. In particular there are certain structures peculiar to the problems that deserve special treatment, and there is ample opportunity for parallel computation. THIS IS BACK COVER TEXT!!! Inverse problems and optimal design have come of age as a consequence of the availability of better, more accurate, and more efficient, simulation packages. The problem of determining the parameters of a physical system from

Editors and Affiliations

  • Chemical Engineering Department, Carnegie Mellon University, Pittsburgh, USA

    Lorenz T. Biegler

  • Computer Science Department, Cornell University, Ithaca, USA

    Thomas F. Coleman

  • Thomas J. Watson Research Center, Yorktown Heights, USA

    Andrew R. Conn

  • School of Mathematics, University of Minnesota, Minneapolis, USA

    Fadil N. Santosa

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