Nonlinear Optimization

AN ASYMPTOTIC VISCOSITY SELECTION RESULT FOR THE REGULARIZED NEWTON DYNAMIC

  • Boushra Abbas
    • Categories Nonlinear Optimization

    Let $\Phi:\mathcal{H}\longrightarrow\mathbb{R\cup}\left\{ +\infty\right\} $ be a closed convex proper function on a real Hilbert space $\mathcal{H}$, and $\partial\Phi:\mathcal{H}\rightrightarrows\mathcal{H}$ its subdifferential. For any control function $\epsilon:\mathbb{R}_{+}\longrightarrow\mathbb{R}_{+}$ which tends to zero as $t$ goes to $+\infty$, and $\lambda$ a positive parameter, we study the asymptotic behavior of the trajectories of the regularized Newton dynamical system \begin{eqnarray*} & … Read more

    A second-order sequential optimality condition associated to the convergence of optimization algorithms

  • Roberto Andreani
  • Gabriel Haeser
  • Alberto Ramos
  • Paulo J. S. Silva
    • Categories Constrained Nonlinear Optimization Tags , ,

    Sequential optimality conditions have recently played an important role on the analysis of the global convergence of optimization algorithms towards first-order stationary points and justifying their stopping criteria. In this paper we introduce the first sequential optimality condition that takes into account second-order information. We also present a companion constraint qualification that is less stringent … Read more

    Strong SOCP Relaxations for the Optimal Power Flow Problem

  • Santanu S. Dey
  • Burak Kocuk
  • Xu Andy Sun
    • Categories Applications - Science and Engineering, Global Optimization, Nonlinear Optimization Tags , , ,

    This paper proposes three strong second order cone programming (SOCP) relaxations for the AC optimal power flow (OPF) problem. These three relaxations are incomparable to each other and two of them are incomparable to the standard SDP relaxation of OPF. Extensive computational experiments show that these relaxations have numerous advantages over existing convex relaxations in … Read more

    A proximal gradient method for ensemble density functional theory

  • Dennis Klöckner
  • Zhaosong Lu
  • Michael Ulbrich
  • Zaiwen Wen
  • Chao Yang
    • Categories Basic Sciences Applications, Constrained Nonlinear Optimization Tags , , ,

    The ensemble density functional theory is valuable for simulations of metallic systems due to the absence of a gap in the spectrum of the Hamiltonian matrices. Although the widely used self-consistent field iteration method can be extended to solve the minimization of the total energy functional with respect to orthogonality constraints, there is no theoretical … Read more

    Bridging the Gap Between Multigrid, Hierarchical, and Receding-Horizon Control

  • Victor M. Zavala
    • Categories Distributed Control, Nonlinear Optimization, Systems governed by Differential Equations Optimization Tags , , , ,

    We analyze the structure of the Euler-Lagrange conditions of a lifted long-horizon optimal control problem. The analysis reveals that the conditions can be solved by using block Gauss-Seidel schemes and we prove that such schemes can be implemented by solving sequences of short-horizon problems. The analysis also reveals that a receding-horizon control scheme is equivalent … Read more

    Stochastic Optimization using a Trust-Region Method and Random Models

  • Ruobing Chen
  • Matt Menickelly
  • Katya Scheinberg
    • Categories Stochastic Programming, Unconstrained Optimization Tags , , ,

    In this paper, we propose and analyze a trust-region model-based algorithm for solving unconstrained stochastic optimization problems. Our framework utilizes random models of an objective function $f(x)$, obtained from stochastic observations of the function or its gradient. Our method also utilizes estimates of function values to gauge progress that is being made. The convergence analysis … Read more

    New results on subgradient methods for strongly convex optimization problems with a unified analysis

  • Masaru Ito
    • Categories Constrained Nonlinear Optimization, Convex Optimization, Nonsmooth Optimization Tags , , , , , ,

    We develop subgradient- and gradient-based methods for minimizing strongly convex functions under a notion which generalizes the standard Euclidean strong convexity. We propose a unifying framework for subgradient methods which yields two kinds of methods, namely, the Proximal Gradient Method (PGM) and the Conditional Gradient Method (CGM), unifying several existing methods. The unifying framework provides … Read more

    Lower Bounds on Complexity of Lyapunov Functions for Switched Linear Systems

  • Amir Ali Ahmadi
  • Raphaël Jungers
    • Categories Convex Optimization, Semi-definite Programming, Systems governed by Differential Equations Optimization Tags , , ,

    We show that for any positive integer $d$, there are families of switched linear systems—in fixed dimension and defined by two matrices only—that are stable under arbitrary switching but do not admit (i) a polynomial Lyapunov function of degree $\leq d$, or (ii) a polytopic Lyapunov function with $\leq d$ facets, or (iii) a piecewise … Read more

    On an adaptive regularization for ill-posed nonlinear systems and its trust-region implementation

  • Stefania Bellavia
  • Benedetta Morini
  • Elisa Riccietti
    • Categories Nonlinear Optimization Tags , , ,

    In this paper we address the stable numerical solution of nonlinear ill-posed systems by a trust-region method. We show that an appropriate choice of the trust-region radius gives rise to a procedure that has the potential to approach a solution of the unperturbed system. This regularizing property is shown theoretically and validated numerically. CitationDipartimento di … Read more

    Convergence rates for forward-backward dynamical systems associated with strongly monotone inclusions

  • Radu Ioan Bot
  • Ernö Robert Csetnek
    • Categories Convex Optimization, Nonsmooth Optimization, Systems governed by Differential Equations Optimization Tags , , , ,

    We investigate the convergence rates of the trajectories generated by implicit first and second order dynamical systems associated to the determination of the zeros of the sum of a maximally monotone operator and a monotone and Lipschitz continuous one in a real Hilbert space. We show that these trajectories strongly converge with exponential rate to … Read more