Constrained Nonlinear Optimization

A Flexible Inexact Restoration Method and Application to Optimization with Multiobjective Constraints under Weighted-Sum Scalarization

  • Luís Felipe Bueno
  • Gabriel Haeser
  • José Mario Martínez
    • Categories Constrained Nonlinear Optimization, Multi-Criteria Optimization

    We introduce a new flexible Inexact-Restoration (IR) algorithm and an application to problems with multiobjective constraints (MOCP) under the weighted-sum scalarization approach. In IR methods each iteration has two phases. In the first phase one aims to improve the feasibility and, in the second phase, one minimizes a suitable objective function. This is done in … Read more

    Mini-batch Stochastic Approximation Methods for Nonconvex Stochastic Composite Optimization

  • Saeed Ghadimi
  • Guanghui Lan
  • Hongchao Zhang
    • Categories Constrained Nonlinear Optimization, Convex and Nonsmooth Optimization Tags , , , , , ,

    This paper considers a class of constrained stochastic composite optimization problems whose objective function is given by the summation of a differentiable (possibly nonconvex) component, together with a certain non-differentiable (but convex) component. In order to solve these problems, we propose a randomized stochastic projected gradient (RSPG) algorithm, in which proper mini-batch of samples are … Read more

    A Sequential Quadratic Optimization Algorithm with Rapid Infeasibility Detection

  • James V. Burke
  • Frank E. Curtis
  • Hao Wang
    • Categories Constrained Nonlinear Optimization, Nonlinear Optimization Tags , , , , ,

    We present a sequential quadratic optimization (SQO) algorithm for nonlinear constrained optimization. The method attains all of the strong global and fast local convergence guarantees of classical SQO methods, but has the important additional feature that fast local convergence is guaranteed when the algorithm is employed to solve infeasible instances. A two-phase strategy, carefully constructed … Read more

    Local Convergence of the Method of Multipliers for Variational and Optimization Problems under the Sole Noncriticality Assumption

  • Alexey F. Izmailov
  • A. S. Kurennoy
  • Mikhail V. Solodov
    • Categories Complementarity and Variational Inequalities, Constrained Nonlinear Optimization Tags , , , , , ,

    We present local convergence analysis of the method of multipliers for equality-constrained variational problems (in the special case of optimization, also called the augmented Lagrangian method) under the sole assumption that the dual starting point is close to a noncritical Lagrange multiplier (which is weaker than second-order sufficiency). Local superlinear convergence is established under the … Read more

    Projected subgradient minimization versus superiorization

  • Yair Censor
  • Ran Davidi
  • Gabor T. Herman
  • Reinhard W. Schulte
  • Luba Tetruashvili
    • Categories Biomedical Applications, Constrained Nonlinear Optimization Tags , , , , , , , ,

    The projected subgradient method for constrained minimization repeatedly interlaces subgradient steps for the objective function with projections onto the feasible region, which is the intersection of closed and convex constraints sets, to regain feasibility. The latter poses a computational difficulty and, therefore, the projected subgradient method is applicable only when the feasible region is “simple … 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

    KKT Reformulation and Necessary Conditions for Optimality in Nonsmooth Bilevel Optimization

  • Stephan Dempe
  • Alain Zemkoho
    • Categories Constrained Nonlinear Optimization, Nonsmooth Optimization Tags , , , , ,

    For a long time, the bilevel programming problem has essentially been considered as a special case of mathematical programs with equilibrium constraints (MPECs), in particular when the so-called KKT reformulation is in question. Recently though, this widespread believe was shown to be false in general. In this paper, other aspects of the difference between both … Read more

    Second-order necessary conditions in Pontryagin form for optimal control problems

  • Joseph Frédéric Bonnans
  • Xavier Dupuis
  • Laurent Pfeiffer
    • Categories Constrained Nonlinear Optimization, Systems governed by Differential Equations Optimization

    In this report, we state and prove first- and second-order necessary conditions in Pontryagin form for optimal control problems with pure state and mixed control-state constraints. We say that a Lagrange multiplier of an optimal control problem is a Pontryagin multiplier if it is such that Pontryagin’s minimum principle holds, and we call optimality conditions … Read more

    Second-order sufficient conditions for strong solutions to optimal control problems

  • Joseph Frédéric Bonnans
  • Xavier Dupuis
  • Laurent Pfeiffer
    • Categories Constrained Nonlinear Optimization, Systems governed by Differential Equations Optimization

    In this report, given a reference feasible trajectory of an optimal control problem, we say that the quadratic growth property for bounded strong solutions holds if the cost function of the problem has a quadratic growth over the set of feasible trajectories with a bounded control and with a state variable sufficiently close to the … Read more

    Robust convex relaxation for the planted clique and densest k-subgraph problems

  • Brendan Ames
    • Categories Constrained Nonlinear Optimization, Convex Optimization, Nonsmooth Optimization Tags , , ,

    We consider the problem of identifying the densest k-node subgraph in a given graph. We write this problem as an instance of rank-constrained cardinality minimization and then relax using the nuclear and l1 norms. Although the original combinatorial problem is NP-hard, we show that the densest k-subgraph can be recovered from the solution of our … Read more