Hessian approximation in multilevel nonlinear optimization

  • Vincent Malmedy

    Student thesis: Doc typesDoctor of Sciences


    This research concerns the algorithmic study of Hessian approximation in the context of multilevel nonlinear optimization problems. Methods using finite-difference approximations or secant equations are here considered. We present new methods for the Hessian approximation and update, and numerically compare their performance with existing methods. A software implementing an efficient method for Hessian approximation in this context has been developed, and is documented in this manuscript. Moreover an application of these developments to the modelling of snake-skin pigmentation patterns is presented.
    Date of Award10 Sep 2010
    Original languageEnglish
    Awarding Institution
    • University of Namur
    SupervisorPhilippe TOINT (Supervisor), Annick Sartenaer (Jury), Serge Gratton (Jury), Andre Fuzfa (Jury), Moritz DIEHL (Jury) & Anne Lemaitre (President)

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