CUTEst: a Constrained and Unconstrained Testing Environment with safe threads

  • Nicholas I. M. Gould
  • Dominique Orban
  • Philippe L. Toint
    • Categories Optimization Software and Modeling Systems Tags ,

    We describe the most recent evolution of our constrained and unconstrained testing environment and its accompanying SIF decoder. Code-named SIFDecode and CUTEst, these updated versions feature dynamic memory allocation, a modern thread-safe Fortran modular design, a new Matlab interface and a revised installation procedure integrated with GALAHAD. CitationTechnical Report Rutherford Appleton Laboratory Chilton, Oxfordshire, England, … Read more

    The proximal-proximal gradient algorithm

  • Ting Kei Pong
    • Categories Applications - Science and Engineering, Convex and Nonsmooth Optimization, Nonlinear Optimization Tags , , , ,

    We consider the problem of minimizing a convex objective which is the sum of a smooth part, with Lipschitz continuous gradient, and a nonsmooth part. Inspired by various applications, we focus on the case when the nonsmooth part is a composition of a proper closed convex function P and a nonzero affine map, with the … Read more

    Solution of Nonlinear Equations via Optimization

  • Isaac Siwale
    • Categories Applications - OR and Management Sciences, Constrained Nonlinear Optimization, Multi-Criteria Optimization Tags , , , , ,

    This paper presents four optimization models for solving nonlinear equation systems. The models accommodate both over-specified and under-specified systems. A variable endogenization technique that improves efficiency is introduced, and a basic comparative study shows one of the methods presented to be very effective. CitationSiwale, I. (2013). Solution of nonlinear equation systems via optimization. Technical Report … Read more

    Efficient random coordinate descent algorithms for large-scale structured nonconvex optimization

  • Ion Necoara
  • Andrei Patrascu
    • Categories Global Optimization, Global Optimization Theory, Nonlinear Optimization

    In this paper we analyze several new methods for solving nonconvex optimization problems with the objective function formed as a sum of two terms: one is nonconvex and smooth, and another is convex but simple and its structure is known. Further, we consider both cases: unconstrained and linearly constrained nonconvex problems. For optimization problems of … Read more

    Kusuoka Representations of Coherent Risk Measures in General Probability Spaces

  • Nilay Noyan
  • Gabor Rudolf
    • Categories Stochastic Programming

    Kusuoka representations provide an important and useful characterization of law invariant coherent risk measures in atomless probability spaces. However, the applicability of these results is limited by the fact that such representations do not always exist in probability spaces with atoms, such as finite probability spaces. We introduce the class of functionally coherent risk measures, … Read more

    Incremental Accelerated Gradient Methods for SVM Classification: Study of the Constrained Approach

  • Nicolas Couellan
  • Sophie Jan
    • Categories Constrained Nonlinear Optimization, Data-Mining Tags , , , , , ,

    We investigate constrained first order techniques for training Support Vector Machines (SVM) for online classification tasks. The methods exploit the structure of the SVM training problem and combine ideas of incremental gradient technique, gradient acceleration and successive simple calculations of Lagrange multipliers. Both primal and dual formulations are studied and compared. Experiments show that the … Read more

    Asymptotic Convergence Analysis for Distributional Robust Optimization and Equilibrium Problems

  • Hailin Sun
  • Huifu Xu
    • Categories Robust Optimization Tags , , ,

    In this paper, we study distributional robust optimization approaches for a one stage stochastic minimization problem, where the true distribution of the underlying random variables is unknown but it is possible to construct a set of probability distributions which contains the true distribution and optimal decision is taken on the basis of worst possible distribution … Read more

    Distributionally robust control of constrained stochastic systems

  • Paul J. Goulart
  • Daniel Kuhn
  • Bart Paul Gerard Van Parys
  • Manfred Morari
    • Categories Control Applications, Robust Optimization Tags , ,

    We investigate the control of constrained stochastic linear systems when faced with only limited information regarding the disturbance process, i.e. when only the first two moments of the disturbance distribution are known. We consider two types of distributionally robust constraints. The constraints of the first type are required to hold with a given probability for … Read more

    Practical Multi-objective Programming

  • Isaac Siwale
    • Categories Applications - OR and Management Sciences Tags , , , , ,

    This paper is on practical solutions to the multi-objective optimization problem; it advocates for single-point solutions either of the Nash equilibrium or the Tchebycheff compromise type, depending on whether one can reasonably ascribe competition or cooperation to the problem at hand. A transform method that greatly simplifies implementation of the compromise solution is presented and … Read more

    An Inexact Sequential Quadratic Optimization Algorithm for Nonlinear Optimization

  • Frank E. Curtis
  • Travis C. Johnson
  • Daniel P. Robinson
  • Andreas Wächter
    • Categories Constrained Nonlinear Optimization Tags , , , ,

    We propose a sequential quadratic optimization method for solving nonlinear optimization problems with equality and inequality constraints. The novel feature of the algorithm is that, during each iteration, the primal-dual search direction is allowed to be an inexact solution of a given quadratic optimization subproblem. We present a set of generic, loose conditions that the … Read more