Optimality conditions and global convergence for nonlinear semidefinite programming

  • Roberto Andreani
  • Gabriel Haeser
  • Daiana O. Santos
    • Categories Nonlinear Optimization, Semi-definite Programming Tags , , ,

    Sequential optimality conditions have played a major role in unifying and extending global convergence results for several classes of algorithms for general nonlinear optimization. In this paper, we extend theses concepts for nonlinear semidefinite programming. We define two sequential optimality conditions for nonlinear semidefinite programming. The first is a natural extension of the so-called Approximate-Karush-Kuhn-Tucker … Read more

    MIQP-Based Algorithm for the Global Solution of Economic Dispatch Problems with Valve-Point Effects

  • Pierre-Antoine Absil
  • Benoît Sluysmans
  • Nicolas Stevens
    • Categories Applications - Science and Engineering, Constrained Nonlinear Optimization, Global Optimization Tags , , , ,

    Even in a static setting, the economic load dispatch problem (ELDP)—namely the cost-optimal distribution of power among generating units to meet a specific demand subject to system constraints—turns out to be a challenge owing to the consideration of valve-point effects (VPE), which make the cost function nonsmooth and nonconvex. We present a new method, termed … Read more

    Dual approach for two-stage robust nonlinear optimization

  • Frans J.C.T. de Ruiter
  • Dick den Hertog
  • Jianzhe Zhen
    • Categories Robust Optimization Tags , , ,

    Adjustable robust minimization problems in which the adjustable variables appear in a convex way are difficult to solve. For example, if we substitute linear decision rules for the adjustable variables, then the model becomes convex in the uncertain parameters, whereas for computational tractability we need concavity in the uncertain parameters. In this paper we reformulate … Read more

    A Stochastic Semismooth Newton Method for Nonsmooth Nonconvex Optimization

  • Shicong Cen
  • Andre Milzarek
  • Michael Ulbrich
  • Zaiwen Wen
  • Xiantao Xiao
    • Categories Nonsmooth Optimization Tags , , , ,

    In this work, we present a globalized stochastic semismooth Newton method for solving stochastic optimization problems involving smooth nonconvex and nonsmooth convex terms in the objective function. We assume that only noisy gradient and Hessian information of the smooth part of the objective function is available via calling stochastic first and second order oracles. The … Read more

    Models and algorithms for the robust resource constrained shortest path problem

  • Fatma Gzara
  • Da Lu
    • Categories Network Optimization, Robust Optimization, Transportation Tags , , ,

    We study the robust resource constrained shortest path problem (RCSPP) under uncertainty in cost and multiple resource consumption. Contrary to the deterministic RCSPP where the cost and the consumption of resources on an arc are known and fixed, the robust RCSPP models the case where both the cost and the resource consumption are random, and … Read more

    Scenario Reduction for Risk-Averse Stochastic Programs

  • Sebastian Arpon
  • Tito Homem-de-Mello
  • Bernardo K. Pagnoncelli
    • Categories Stochastic Programming

    In this paper we discuss scenario reduction methods for risk-averse stochastic optimization problems. Scenario reduction techniques have received some attention in the literature and are used by practitioners, as such methods allow for an approximation of the random variables in the problem with a moderate number of scenarios, which in turn make the optimization problem … Read more

    Superiorization and perturbation resilience of algorithms: A continuously updated bibliography

  • Yair Censor
    • Categories Biomedical Applications, Constrained Nonlinear Optimization Tags ,

    This document presents a, chronologically ordered, bibliography of scientific publications on the superiorization methodology and perturbation resilience of algorithms which is compiled and continuously updated by us at: http://math.haifa.ac.il/yair/bib-superiorization-censor.html. Since the topic is relatively new it is possible to trace the work that has been published about it since its inception. To the best of … Read more

    Approximation Algorithms for D-optimal Design

  • Mohit Singh
  • Weijun Xie
    • Categories Combinatorial Optimization

    Experimental design is a classical statistics problem and its aim is to estimate an unknown m-dimensional vector from linear measurements where a Gaussian noise is introduced in each measurement. For the combinatorial experimental design problem, the goal is to pick k out of the given n experiments so as to make the most accurate estimate … Read more

    A comparison of methods for traversing non-convex regions in optimization problems

  • Michael Bartholomew-Biggs
  • Salah Beddiaf
  • Bruce Christianson
    • Categories Unconstrained Optimization Tags , ,

    This paper considers again the well-known problem of dealing with non-convex regions during the minimization of a nonlinear function F(x) by Newton-like methods. The proposal made here involves a curvilinear search along an approximation to the continuous steepest descent path defined by the solution of the ODE dx/dt = -grad F(x). The algorithm we develop … Read more

    A finite ε-convergence algorithm for two-stage convex 0-1 mixed-integer nonlinear stochastic programs with mixed-integer first and second stage variables

  • Ignacio E. Grossmann
  • Can Li
    • Categories Stochastic Programming Tags , , ,

    In this paper, we propose a generalized Benders decomposition-based branch and bound algorithm, GBDBAB, to solve two-stage convex 0-1 mixed-integer nonlinear stochastic programs with mixed-integer variables in both first and second stage decisions. In order to construct the convex hull of the MINLP subproblem for each scenario in closed-form, we first represent each MINLP subproblem … Read more