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An Interior-Point Algorithm for Large Scale Optimization

  • John T. Betts
  • Samuel K. Eldersveld
  • Paul D. Frank
  • John G. Lewis
Part of the Lecture Notes in Computational Science and Engineering book series (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.

Keywords

Nonlinear Program Merit Function Central Path Barrier Method Large Scale Optimization 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • John T. Betts
    • 1
  • Samuel K. Eldersveld
    • 2
  • Paul D. Frank
    • 1
  • John G. Lewis
    • 1
  1. 1.Mathematics and Engineering AnalysisThe Boeing CompanySeattle
  2. 2.Expedia, Inc.Bellevue

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