Nonlinear Optimization

On generalized-convex constrained multi-objective optimization

  • Christian Günther
  • Christiane Tammer
    • Categories Constrained Nonlinear Optimization, Generalized Convexity/Monoticity, Multi-Criteria Optimization Tags , , , , ,

    In this paper, we consider multi-objective optimization problems involving not necessarily convex constraints and componentwise generalized-convex (e.g., semi-strictly quasi-convex, quasi-convex, or explicitly quasi-convex) vector-valued objective functions that are acting between a real linear topological pre-image space and a finite dimensional image space. For these multi-objective optimization problems, we show that the set of (strictly, weakly) … Read more

    Automatic Differentiation of the Open CASCADE Technology CAD System and its coupling with an Adjoint CFD Solver

  • Salvatore Auriemma
  • Herve Legrand
  • Mladen Banovic
  • Jens-Dominik Müller
  • Orest Mykhaskiv
  • Andrea Walther
    • Categories Optimization of Systems modeled by PDEs, Unconstrained Optimization Tags , , ,

    Automatic Differentiation (AD) is applied to the open-source CAD system Open CASCADE Technology using the AD software tool ADOL-C (Automatic Differentiation by OverLoading in C++). The differentiated CAD system is coupled with a discrete adjoint CFD solver, thus providing the first example of a complete differentiated design chain built from generic, multi-purpose tools. The design … Read more

    Linear Convergence of Proximal Incremental Aggregated Gradient Methods under Quadratic Growth Condition

  • Hui Zhang
    • Categories Constrained Nonlinear Optimization, Convex Optimization, Nonsmooth Optimization Tags , , , , ,

    Under the strongly convex assumption, several recent works studied the global linear convergence rate of the proximal incremental aggregated gradient (PIAG) method for minimizing the sum of a large number of smooth component functions and a non-smooth convex function. In this paper, under the quadratic growth condition{a strictly weaker condition than the strongly convex assumption, … Read more

    Dantzig Wolfe decomposition and objective function convexification for binary quadratic problems: the cardinality constrained quadratic knapsack case

  • Alberto Ceselli
  • Lucas Létocart
  • Emiliano Traversi
    • Categories (Mixed) Integer Nonlinear Programming, Combinatorial Optimization, Quadratic Programming Tags , , ,

    The purpose of this paper is to provide strong reformulations for binary quadratic problems. We propose a first methodological analysis on a family of reformulations combining Dantzig-Wolfe decomposition and Quadratic Convex Reformulation principles. As a representative case study, we apply them to a cardinality constrained quadratic knapsack problem, providing extensive experimental insights. We show that … Read more

    A randomized method for smooth convex minimization, motivated by probability maximization

  • Csaba I. Fábián
  • Tamas Szantai
    • Categories Nonlinear Optimization, Stochastic Programming Tags , ,

    We propose a randomized gradient method – or a randomized cutting-plane method from a dual viewpoint. From the primal viewpoint, our method bears a resemblance to the stochastic approximation family. But in contrast to stochastic approximation, the present method builds a model problem. CitationKecskemet College, Pallasz Athene University. Izsaki ut 10, 6000 Kecskemet, Hungary; and … Read more

    An Active-Set Algorithmic Framework for Non-Convex Optimization Problems over the Simplex

  • Andrea Cristofari
  • Marianna De Santis
  • Stefano Lucidi
  • Francesco Rinaldi
    • Categories Nonlinear Optimization

    In this paper, we describe a new active-set algorithmic framework for minimizing a non-convex function over the unit simplex. At each iteration, the method makes use of a rule for identifying active variables (i.e., variables that are zero at a stationary point) and specific directions (that we name active-set gradient related directions) satisfying a new … Read more

    Direct Search Methods on Reductive Homogeneous Spaces

  • Dreisigmeyer David
    • Categories Nonlinear Optimization, Nonsmooth Optimization Tags ,

    Direct search methods are mainly designed for use in problems with no equality constraints. However, there are many instances where the feasible set is of measure zero in the ambient space and no mesh point lies within it. There are methods for working with feasible sets that are (Riemannian) manifolds, but not all manifolds are … Read more

    A block symmetric Gauss-Seidel decomposition theorem for convex composite quadratic programming and its applications

  • Xudong Li
  • Defeng Sun
  • Kim-Chuan Toh
    • Categories Nonsmooth Optimization, Quadratic Programming Tags , ,

    For a symmetric positive semidefinite linear system of equations $\mathcal{Q} {\bf x} = {\bf b}$, where ${\bf x} = (x_1,\ldots,x_s)$ is partitioned into $s$ blocks, with $s \geq 2$, we show that each cycle of the classical block symmetric Gauss-Seidel (block sGS) method exactly solves the associated quadratic programming (QP) problem but added with an … Read more

    BFGS convergence to nonsmooth minimizers of convex functions

  • Jiayi Guo
  • Adrian Lewis
    • Categories Nonsmooth Optimization, Unconstrained Optimization

    The popular BFGS quasi-Newton minimization algorithm under reasonable conditions converges globally on smooth convex functions. This result was proved by Powell in 1976: we consider its implications for functions that are not smooth. In particular, an analogous convergence result holds for functions, like the Euclidean norm, that are nonsmooth at the minimizer. CitationManuscript: School of … Read more

    Speed optimization over a path with heterogeneous arc costs

  • Qie He
  • Kameng Nip
  • Zhang Xiaochen
    • Categories Convex Optimization, Nonlinear Optimization, Transportation

    The speed optimization problem over a path aims to find a set of speeds over each arc of the given path to minimize the total cost, while respecting the time-window constraint at each node and speed limits over each arc. In maritime transportation, the cost represents fuel cost or emissions, so study of this problem … Read more