Roger Behling

Local convergence analysis of the Levenberg-Marquardt framework for nonzero-residue nonlinear least-squares problems under an error bound condition

  • Roger Behling
  • Douglas S. Gonçalves
  • Sandra Augusta Santos
    • Categories Nonlinear Systems and Least-Squares

    The Levenberg-Marquardt method (LM) is widely used for solving nonlinear systems of equations, as well as nonlinear least-squares prob- lems. In this paper, we consider local convergence issues of the LM method when applied to nonzero-residue nonlinear least-squares problems under an error bound condition, which is weaker than requiring full-rank of the Jacobian in a … Read more

    A Special Complementarity Function Revisited

  • Roger Behling
  • Andreas Fischer
  • Klaus Schönefeld
  • Nico Strasdat
    • Categories Complementarity and Variational Inequalities, Nonlinear Optimization Tags , , ,

    Recently, a local framework of Newton-type methods for constrained systems of equations has been developed which, applied to the solution of Karush-KuhnTucker (KKT) systems, enables local quadratic convergence under conditions that allow nonisolated and degenerate KKT points. This result is based on a reformulation of the KKT conditions as a constrained piecewise smooth system of … Read more

    On a conjecture in second-order optimality conditions

  • Roger Behling
  • Gabriel Haeser
  • Alberto Ramos
  • Daiana O. Santos
    • Categories Constrained Nonlinear Optimization Tags , , ,

    In this paper we deal with optimality conditions that can be verified by a nonlinear optimization algorithm, where only a single Lagrange multiplier is avaliable. In particular, we deal with a conjecture formulated in [R. Andreani, J.M. Martinez, M.L. Schuverdt, “On second-order optimality conditions for nonlinear programming”, Optimization, 56:529–542, 2007], which states that whenever a … Read more

    On Second Order Optimality Conditions in Nonlinear Optimization

  • Roberto Andreani
  • Roger Behling
  • Gabriel Haeser
  • Paulo J. S. Silva
    • Categories Constrained Nonlinear Optimization, Nonlinear Optimization

    In this work we present new weak conditions that ensure the validity of necessary second order optimality conditions (SOC) for nonlinear optimization. We are able to prove that weak and strong SOCs hold for all Lagrange multipliers using Abadie-type assumptions. We also prove weak and strong SOCs for at least one Lagrange multiplier imposing the … Read more

    Primal-dual relationship between Levenberg-Marquardt and central trajectories for linearly constrained convex optimization

  • Roger Behling
  • Clóvis Caesar Gonzaga
  • Gabriel Haeser
    • Categories Convex Optimization, Quadratic Programming Tags , , , , , ,

    We consider the minimization of a convex function on a compact polyhedron defined by linear equality constraints and nonnegative variables. We define the Levenberg-Marquardt (L-M) and central trajectories starting at the analytic center and using the same parameter, and show that they satisfy a primal-dual relationship, being close to each other for large values of … Read more