Constrained Nonlinear Optimization

A parallelizable augmented Lagrangian method applied to large-scale non-convex-constrained optimization problems

  • Natashia Boland
  • Brian Dandurand
  • Andrew C. Eberhard
  • Fabricio Oliveira
  • Jeffrey Christiansen
    • Categories (Mixed) Integer Nonlinear Programming, Constrained Nonlinear Optimization, Parallel Algorithms Tags , , , ,

    We contribute improvements to a Lagrangian dual solution approach applied to large-scale optimization problems whose objective functions are convex, continuously differentiable and possibly nonlinear, while the non-relaxed constraint set is compact but not necessarily convex. Such problems arise, for example, in the split-variable deterministic reformulation of stochastic mixed-integer optimization problems. The dual solution approach needs … Read more

    Efficient solution of quadratically constrained quadratic subproblems within the MADS algorithm

  • Nadir Amaioua
  • Charles Audet
  • Andrew R. Conn
  • Sébastien Le Digabel
    • Categories Constrained Nonlinear Optimization, Nonsmooth Optimization

    The Mesh Adaptive Direct Search algorithm (MADS) is an iterative method for constrained blackbox optimization problems. One of the optional MADS features is a versatile search step in which quadratic models are built leading to a series of quadratically constrained quadratic subproblems. This work explores different algorithms that exploit the structure of the quadratic models: … Read more

    Numerical solution of optimal control problems with explicit and implicit switches

  • Hans Georg Bock
  • Christian Kirches
  • Andreas Meyer
  • Andreas Potschka
    • Categories Constrained Nonlinear Optimization, Systems governed by Differential Equations Optimization

    In this article, we present a unified framework for the numerical solution of optimal control problems constrained by ordinary differential equations with both implicit and explicit switches. We present the problem class and qualify different types of implicitly switched systems. This classification significantly affects opportunities for solving such problems numerically. By using techniques from generalized … Read more

    Sequential Linear Programming and Particle Swarm Optimization for the optimization of energy districts

  • Stefania Bellavia
  • Elisa Riccietti
  • Stefano Sello
    • Categories Basic Sciences Applications, Constrained Nonlinear Optimization, Nonlinear Optimization Tags , , ,

    In this paper we deal with the optimization of energy resources management of industrial districts, with the aim of minimizing the customer energy expenses. In a district the number of possible energy system combinations is really large, and a manual design approach might lead to a suboptimal solution. For this reason we designed a software … Read more

    A second-order optimality condition with first- and second-order complementarity associated with global convergence of algorithms

  • Gabriel Haeser
    • Categories Constrained Nonlinear Optimization Tags , , ,

    We develop a new notion of second-order complementarity with respect to the tangent subspace related to second-order necessary optimality conditions by the introduction of so-called tangent multipliers. We prove that around a local minimizer, a second-order stationarity residual can be driven to zero while controlling the growth of Lagrange multipliers and tangent multipliers, which gives … Read more

    Can linear superiorization be useful for linear optimization problems?

  • Yair Censor
    • Categories Constrained Nonlinear Optimization, Linear Programming, Problem Solving Environments Tags , , , , , , , , ,

    Linear superiorization considers linear programming problems but instead of attempting to solve them with linear optimization methods it employs perturbation resilient feasibility-seeking algorithms and steers them toward reduced (not necessarily minimal) target function values. The two questions that we set out to explore experimentally are (i) Does linear superiorization provide a feasible point whose linear … Read more

    Linear superiorization for infeasible linear programming

  • Yair Censor
  • Yehuda Zur
    • Categories Constrained Nonlinear Optimization, Linear Programming

    Linear superiorization (abbreviated: LinSup) considers linear programming (LP) problems wherein the constraints as well as the objective function are linear. It allows to steer the iterates of a feasibility-seeking iterative process toward feasible points that have lower (not necessarily minimal) values of the objective function than points that would have been reached by the same … Read more

    A New First-order Algorithmic Framework for Optimization Problems with Orthogonality Constraints

  • Xiaojun Chen
  • Bin Gao
  • Xin Liu
  • Ya-xiang Yuan
    • Categories Basic Sciences Applications, Constrained Nonlinear Optimization Tags , , , , ,

    In this paper, we consider a class of optimization problems with orthogonality constraints, the feasible region of which is called the Stiefel manifold. Our new framework combines a function value reduction step with a correction step. Different from the existing approaches, the function value reduction step of our algorithmic framework searches along the standard Euclidean … Read more

    Low-complexity method for hybrid MPC with local guarantees

  • Alexander Domahidi
  • Angelos Georghiou
  • Damian Frick
  • Juan L. Jerez
  • Manfred Morari
    • Categories Constrained Nonlinear Optimization, Control Applications Tags , , ,

    Model predictive control problems for constrained hybrid systems are usually cast as mixed-integer optimization problems (MIP). However, commercial MIP solvers are designed to run on desktop computing platforms and are not suited for embedded applications which are typically restricted by limited computational power and memory. To alleviate these restrictions, we develop a novel low-complexity, iterative … Read more

    A Study of the Difference-of-Convex Approach for Solving Linear Programs with Complementarity Constraints

  • Francisco Jara-Moroni
  • Jong-Shi Pang
    • Categories Complementarity and Variational Inequalities, Constrained Nonlinear Optimization Tags , , ,

    This paper studies the difference-of-convex (DC) penalty formulations and the associated difference-of-convex algorithm (DCA) for computing stationary solutions of linear programs with complementarity constraints (LPCCs). We focus on three such formulations and establish connections between their stationary solutions and those of the LPCC. Improvements of the DCA are proposed to remedy some drawbacks in a … Read more