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Global Convergence of a Non-monotone Trust-Region Filter Algorithm for Nonlinear Programming

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Multiscale Optimization Methods and Applications

Part of the book series: Nonconvex Optimization and Its Applications ((NOIA,volume 82))

Summary

A non-monotone variant of the trust-region SQP-filter algorithm analyzed in Fletcher et al (SIAM J. Opt. 13(3), 2002, pp. 653–659) is defined, that directly uses the dominated area of the filter as an acceptability criterion for trial points. It is proved that, under reasonable assumptions and for all possible choices of the starting point, the algorithm generates at least a subsequence converging to a first-order critical point.

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Author information

Authors and Affiliations

  1. Rutherford Appleton Laboratory, Computational Science and Engineering Department, Chilton, Oxfordshire, England

    Nicholas I. M. Gould

  2. Department of Mathematics, University of Namur, 61, rue de Bruxelles, B-5000, Namur, Belgium

    Philippe L. Toint

Authors
  1. Nicholas I. M. Gould
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  2. Philippe L. Toint
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Editor information

Editors and Affiliations

  1. University of Florida, Gainesville, Florida

    William W. Hager , Shu-Jen Huang , Panos M. Pardalos  & Oleg A. Prokopyev , ,  & 

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© 2006 Springer Science+Business Media, Inc.

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Gould, N.I.M., Toint, P.L. (2006). Global Convergence of a Non-monotone Trust-Region Filter Algorithm for Nonlinear Programming. In: Hager, W.W., Huang, SJ., Pardalos, P.M., Prokopyev, O.A. (eds) Multiscale Optimization Methods and Applications. Nonconvex Optimization and Its Applications, vol 82. Springer, Boston, MA. https://doi.org/10.1007/0-387-29550-X_5

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