Les méthodes de filtre en optimisation non-linéaire : une comparaison des variantes avec recherche linéaire et région de confiance

    Student thesis: Master typesMaster in Mathematics

    Abstract

    This work deals with a theoretical analysis of the filter methods for nonlinear constrained optimization problems, which aim at avoiding the use of merit functions. The main difference of the studied algorithms is an approach based on trust region or on line search. For the two trust region methods, the global convergence to first-order critical points is proved. The third method, considering a line search, has the advantage to extend to the local convergence to points that satisfy the second order optimality conditions thanks to second order correction steps. In the three approaches, we decompose the step to the next iterate into its normal and tangential components. A comparison of these methods is proposed on a theoretical plan in a last chapter.
    Date of AwardJun 2002
    Original languageFrench
    SupervisorPhilippe TOINT (Supervisor), ANNICK SARTENAER (Co-Supervisor), Benoît Colson (Jury) & Jean-Jacques STRODIOT (Jury)

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