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Topics in Numerical Analysis pp 49–60Cite as

A Box-Constrained Optimization Algorithm with Negative Curvature Directions and Spectral Projected Gradients

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Part of the book series: Computing Supplementa ((COMPUTING,volume 15))

Abstract

A practical algorithm for box-constrained optimization is introduced. The algorithm combines an active-set strategy with spectral projected gradient iterations. In the interior of each face a strategy that deals efficiently with negative curvature is employed. Global convergence results are given. Numerical results are presented.

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Author information

Authors and Affiliations

  1. Department of Computer Science IME-USP, University of São Paulo, Rua do Matão 1010, Cidade Universitária, 05508-900, São Paulo, SP, Brazil

    E. G. Birgin

  2. Department of Applied Mathematics IMECC-UNICAMP, University of Campinas, CP 6065, 13081-970, Campinas, SP, Brazil

    J. M. Martínez

Authors
  1. E. G. Birgin
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  2. J. M. Martínez
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Editor information

Editors and Affiliations

  1. Institut für Angewandte Mathematik, Universität Karlsruhe, Karlsruhe, Germany

    Goetz Alefeld

  2. Department of Mathematical Sciences, Shimane University, Matsue, Japan

    Xiaojun Chen

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© 2001 Springer-Verlag Wien

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Birgin, E.G., Martínez, J.M. (2001). A Box-Constrained Optimization Algorithm with Negative Curvature Directions and Spectral Projected Gradients. In: Alefeld, G., Chen, X. (eds) Topics in Numerical Analysis. Computing Supplementa, vol 15. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6217-0_5

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  • DOI: https://doi.org/10.1007/978-3-7091-6217-0_5

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-83673-6

  • Online ISBN: 978-3-7091-6217-0

  • eBook Packages: Springer Book Archive

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