Numerical experience with a recursive trust-region method for multilevel nonlinear bound-constrained optimization

Serge Gratton, Mélodie Mouffe, Annick Sartenaer, Philippe Toint, Dimitri Tomanos

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Abstract

We consider an implementation of the recursive multilevel trust-region algorithm proposed by Gratton et al. (A recursive trust-region method in infinity norm for bound-constrained nonlinear optimization, IMA J. Numer. Anal. 28(4) (2008), pp. 827-861) for bound-constrained nonlinear problems, and provide numerical experience on multilevel test problems. A suitable choice of the algorithm's parameters is identified on these problems, yielding a satisfactory compromise between reliability and efficiency. The resulting default algorithm is then compared with alternative optimization techniques such as mesh refinement and direct solution of the fine-level problem. It is also shown that its behaviour is similar to that of multigrid algorithms for linear systems.
Original languageEnglish
Pages (from-to)359-386
Number of pages28
JournalOptimization Methods and Software
Volume25
Issue number3
DOIs
Publication statusPublished - 1 Jun 2010

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  • Projects

    Multiscale nonlinear optimization

    SARTENAER, A., TOINT, P., Malmedy, V., Tomanos, D. & Weber Mendonca, M.

    1/07/0431/07/11

    Project: Research

    Activities

    • 1 Oral presentation

    Multilevel optimization using trust-regions and linesearches

    Philippe Toint (Invited speaker)

    12 Nov 2015

    Activity: Talk or presentation typesOral presentation

    Prizes

    Oliver Smithies Fellow

    TOINT, Philippe (Recipient), Sep 2015

    Prize: Fellowship awarded competitively

    Cite this