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An Interior-Point Algorithm for Large Scale Optimization

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Large-Scale PDE-Constrained Optimization

Part of the book series: Lecture Notes in Computational Science and Engineering ((LNCSE,volume 30))

Abstract

This paper describes an interior-point algorithm for solving large scale nonlinear programming problems. The fundamental step of the algorithm requires solution of a sparse symmetric indefinite linear system. Rowand column scaling are used to ensure that the system is well-conditioned. A globalization strategy based on a nonlinear filter is used instead of a merit function. The computational performance of the algorithm is demonstrated on a high index partial differential- algebraic equation application.

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References

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Author information

Authors and Affiliations

  1. Mathematics and Engineering Analysis, The Boeing Company, P.O. Box 3707, MC 7L-21, Seattle, Washington, 98124-2207

    John T. Betts, Paul D. Frank & John G. Lewis

  2. Expedia, Inc., 13810 SE Eastgate Way, Suite 400, Bellevue, WA, 98005

    Samuel K. Eldersveld

Authors
  1. John T. Betts
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  2. Samuel K. Eldersveld
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  3. Paul D. Frank
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  4. John G. Lewis
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Editor information

Editors and Affiliations

  1. Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213, USA

    Lorenz T. Biegler

  2. Department of Computational and Applied Mathematics, Rice University, 6100 S. Main Street — MS134, Houston, TX, 77005, USA

    Matthias Heinkenschloss

  3. Department of Biomedical Engineering and Civil & Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213, USA

    Omar Ghattas

  4. Optimization & Uncertainty Estimation Dept., Sandia National Laboratories — MS 0847, P.O. Box 5800, Albuquerque, NM, 87185, USA

    Bart van Bloemen Waanders

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© 2003 Springer-Verlag Berlin Heidelberg

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Betts, J.T., Eldersveld, S.K., Frank, P.D., Lewis, J.G. (2003). An Interior-Point Algorithm for Large Scale Optimization. In: Biegler, L.T., Heinkenschloss, M., Ghattas, O., van Bloemen Waanders, B. (eds) Large-Scale PDE-Constrained Optimization. Lecture Notes in Computational Science and Engineering, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55508-4_11

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  • DOI: https://doi.org/10.1007/978-3-642-55508-4_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-05045-2

  • Online ISBN: 978-3-642-55508-4

  • eBook Packages: Springer Book Archive

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