Convex and Nonsmooth Optimization

Distributionally robust expectation inequalities for structured distributions

  • Paul J. Goulart
  • Bart Paul Gerard Van Parys
  • Manfred Morari
    • Categories Convex Optimization, Semi-definite Programming, Stochastic Programming Tags , , ,

    Quantifying the risk of unfortunate events occurring, despite limited distributional information, is a basic problem underlying many practical questions. Indeed, quantifying constraint violation probabilities in distributionally robust programming or judging the risk of financial positions can both be seen to involve risk quantification, notwithstanding distributional ambiguity. In this work we discuss worst-case probability and conditional … Read more

    First order optimality conditions for mathematical programs with second-order cone complementarity constraints

  • Jane J. Ye
  • Jinchuan Zhou
    • Categories Complementarity and Variational Inequalities, Nonsmooth Optimization, Second-Order Cone Programming Tags , , , , ,

    In this paper we consider a mathematical program with second-order cone complementarity constraints (SOCMPCC). The SOCMPCC generalizes the mathematical program with complementarity constraints (MPCC) in replacing the set of nonnegative reals by a second-order cone. We show that if the SOCMPCC is considered as an optimization problem with convex cone constraints, then Robinson’s constraint qualification … Read more

    An O(1/k) Convergence Rate for the Variable Stepsize Bregman Operator Splitting Algorithm

  • William W. Hager
  • Maryam Yashtini
  • Hongchao Zhang
    • Categories Nonsmooth Optimization Tags , , , , ,

    An earlier paper proved the convergence of a variable stepsize Bregman operator splitting algorithm (BOSVS) for minimizing $\phi(Bu)+H(u)$ where $H$ and $\phi$ are convex functions, and $\phi$ is possibly nonsmooth. The algorithm was shown to be relatively efficient when applied to partially parallel magnetic resonance image reconstruction problems. In this paper, the convergence rate of … Read more

    Some Applications of Polynomial Optimization in Operations Research and Real-Time Decision Making

  • Amir Ali Ahmadi
  • Anirudha Majumdar
    • Categories Convex Optimization, Global Optimization, Linear, Cone and Semidefinite Programming Tags , , , ,

    We demonstrate applications of algebraic techniques that optimize and certify polynomial inequalities to problems of interest in the operations research and transportation engineering communities. Three problems are considered: (i) wireless coverage of targeted geographical regions with guaranteed signal quality and minimum transmission power, (ii) computing real-time certificates of collision avoidance for a simple model of … Read more

    Decomposition algorithm for large-scale two-stage unit-commitment

  • Jérôme Malick
  • Wim van Ackooij
    • Categories Applications - OR and Management Sciences, Nonsmooth Optimization, Stochastic Programming Tags , , , , ,

    Everyday, electricity generation companies submit a generation schedule to the grid operator for the coming day; computing an optimal schedule is called the unit-commitment problem. Generation companies can also occasionally submit changes to the schedule, that can be seen as intra-daily incomplete recourse actions. In this paper, we propose a two-stage formulation of unit-commitment, wherein … Read more

    Preconditioning of a Generalized Forward-Backward Splitting and Application to Optimization on Graphs

  • Loïc Landrieu
  • Hugo Raguet
    • Categories Convex and Nonsmooth Optimization, Generalized Convexity/Monoticity

    We present a preconditioning of a generalized forward-backward splitting algorithm for finding a zero of a sum of maximally monotone operators \sum_{i=1}^n A_i + B with B cocoercive, involving only the computation of B and of the resolvent of each A_i separately. This allows in particular to minimize functionals of the form \sum_{i=1}^n g_i + … Read more

    Linearly Convergent Away-Step Conditional Gradient for Non-strongly Convex Functions

  • Amir Beck
  • Shimrit Shtern
    • Categories Convex Optimization

    We consider the problem of minimizing a function, which is the sum of a linear function and a composition of a strongly convex function with a linear transformation, over a compact polyhedral set. Jaggi and Lacoste-Julien [14] showed that the conditional gradient method with away steps employed on the aforementioned problem without the additional linear … Read more

    Distributed Gradient Methods with Variable Number of Working Nodes

  • Dragana Bajović
  • Dušan Jakovetić
  • Nataša Krejić
  • Nataša Krklec Jerinkić
    • Categories Convex Optimization, Network Optimization Tags , , , ,

    We consider distributed optimization where $N$ nodes in a connected network minimize the sum of their local costs subject to a common constraint set. We propose a distributed projected gradient method where each node, at each iteration $k$, performs an update (is active) with probability $p_k$, and stays idle (is inactive) with probability $1-p_k$. Whenever … 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