Ademir A. Ribeiro

A practical second-order optimality condition for cardinality-constrained problems with application to an augmented Lagrangian method

  • Jean C. A. Medeiros
  • Ademir A. Ribeiro
  • Mael Sachine
  • Leonardo D. Secchin
    • Categories Nonlinear Optimization Tags , ,

    This paper addresses the mathematical programs with cardinality constraints (MPCaC). We first define two new tailored (strong and weak) second-order necessary conditions, MPCaC-SSONC and MPCaC-WSONC. We then propose a constraint qualification (CQ), namely, MPCaC-relaxed constant rank constraint qualification (MPCaC-RCRCQ), and establish the validity of MPCaC-SSONC at minimizers under this new CQ. All proposed concepts are … Read more

    On the convergence of augmented Lagrangian strategies for nonlinear programming

  • Roberto Andreani
  • A. R. V. Cárdenas
  • Alberto Ramos
  • Ademir A. Ribeiro
  • Leonardo D. Secchin
    • Categories Nonlinear Optimization Tags , , , ,

    Augmented Lagrangian algorithms are very popular and successful methods for solving constrained optimization problems. Recently, the global convergence analysis of these methods have been dramatically improved by using the notion of the sequential optimality conditions. Such conditions are optimality conditions independently of the fulfilment of any constraint qualifications and provide theoretical tools to justify stopping … Read more

    Theoretical aspects of adopting exact penalty elements within sequential methods for nonlinear programming

  • Ademir A. Ribeiro
  • Sandra Augusta Santos
  • Mael Sachine
    • Categories Constrained Nonlinear Optimization

    In the context of sequential methods for solving general nonlinear programming problems, it is usual to work with augmented subproblems instead of the original ones, tackled by the $\ell_1$-penalty function together with the shortcut usage of a convenient penalty parameter. This paper addresses the theoretical reasoning behind handling the original subproblems by such an augmentation … Read more

    Global convergence of trust-region algorithms for constrained minimization without derivatives

  • Paulo Conejo
  • Elizabeth Wegner Karas
  • Lucas G. Pedroso
  • Ademir A. Ribeiro
  • Mael Sachine
    • Categories Constrained Nonlinear Optimization, Nonlinear Optimization

    In this work we propose a trust-region algorithm for the problem of minimizing a function within a convex closed domain. We assume that the objective function is differentiable but no derivatives are available. The algorithm has a very simple structure and allows a great deal of freedom in the choice of the models. Under reasonable … Read more

    Global convergence of slanting filter methods for nonlinear programming

  • Elizabeth Wegner Karas
  • Ademir A. Ribeiro
  • Ana Paula Oening
    • Categories Constrained Nonlinear Optimization Tags , ,

    In this paper we present a general algorithm for nonlinear programming which uses a slanting filter criterion for accepting the new iterates. Independently of how these iterates are computed, we prove that all accumulation points of the sequence generated by the algorithm are feasible. Computing the new iterates by the inexact restoration method, we prove … Read more

    On the convergence rate of the Cauchy algorithm in the l2 norm

  • Elizabeth Wegner Karas
  • Ademir A. Ribeiro
  • Alessandra M. Mota
    • Categories Nonlinear Optimization, Unconstrained Optimization Tags , ,

    This paper presents a convergence rate for the sequence generated by the Cauchy algorithm. The method is applied to a convex quadratic function with exact line search. Instead of using the norm induced by the hessian matrix, the q-linear convergence is shown for the l2 (or Euclidean) norm. CitationTecnhical Report, Dep. Mathematics, Federal University of … Read more