Global Optimization

The complexity of simple models – a study of worst and typical hard cases for the Standard Quadratic Optimization Problem

  • Immanuel M. Bomze
  • Werner Schachinger
  • Reinhard Ullrich
    • Categories Game Theory, Global Optimization Theory, Quadratic Programming

    In a Standard Quadratic Optimization Problem (StQP), a possibly indefinite quadratic form (the simplest nonlinear function) is extremized over the standard simplex, the simplest polytope. Despite this simplicity, the nonconvex instances of this problem class allow for remarkably rich patterns of coexisting local solutions, which are closely related to practical difficulties in solving StQPs globally. … Read more

    Virtuous smoothing for global optimization

  • Jon Lee
  • Daphne Skipper
    • Categories Convex and Nonsmooth Optimization, Global Optimization, Nonlinear Optimization Tags , , , ,

    In the context of global optimization and mixed-integer non-linear programming, generalizing a technique of D’Ambrosio, Fampa, Lee and Vigerske for handling the square-root function, we develop a virtuous smoothing method, using cubics, aimed at functions having some limited non-smoothness. Our results pertain to root functions ($w^p$ with $0

    Global optimal control with the direct multiple shooting method

  • Holger Diedam
  • Sebastian Sager
    • Categories Global Optimization Applications, Global Optimization Theory, Systems governed by Differential Equations Optimization Tags , ,

    We propose to solve global optimal control problems with a new algorithm that is based on Bock’s direct multiple shooting method. We provide conditions and numerical evidence for a significant overall runtime reduction compared to the standard single shooting approach. CitationOptimal Control Applications and Methods, Vol. 39 (2), pp. 449–470, 2017 DOI 10.1002/oca.2324 Article online … Read more

    SCIP: Global Optimization of Mixed-Integer Nonlinear Programs in a Branch-and-Cut Framework

  • Ambros Gleixner
  • Stefan Vigerske
    • Categories (Mixed) Integer Nonlinear Programming, Global Optimization

    This paper describes the extensions that were added to the constraint integer programming framework SCIP in order to enable it to solve convex and nonconvex mixed-integer nonlinear programs (MINLPs) to global optimality. SCIP implements a spatial branch-and-bound algorithm based on a linear outer-approximation, which is computed by convex over- and underestimation of nonconvex functions. An … Read more

    A Modeling-based Approach for Non-standard Packing Problems

  • Giorgio Fasano
    • Categories (Mixed) Integer Linear Programming, Applications - Science and Engineering, Global Optimization

    This chapter examines the problem of packing tetris-like items, orthogonally, with the possibility of rotations, into a convex domain, in the presence of additional conditions. An MILP (Mixed Integer Linear Programming) and an MINLP (Mixed Integer Nonlinear Programming) models, previously studied by the author, are surveyed. An efficient formulation of the objective function, aimed at … Read more

    Globally Optimized Finite Packings of Arbitrary Size Spheres in R^d

  • Ignacio Castillo
  • Frank J. Kampas
  • János Pintér
    • Categories Applications - Science and Engineering, Global Optimization Applications, Optimization Software Benchmark

    This work discusses the following general packing problem-class: given a finite collection of d-dimensional spheres with arbitrarily chosen radii, find the smallest sphere in R^d that contains the entire collection of these spheres in a non-overlapping arrangement. Generally speaking, analytical solution approaches cannot be expected to apply to this general problem-type, except for very small … Read more

    Nonlinear Regression Analysis by Global Optimization: A Case Study in Space Engineering

  • Alessandro Castellazzo
  • Giorgio Fasano
  • János Pintér
  • Mariachiara Vola
    • Categories Applications - Science and Engineering, Global Optimization Applications, Optimization Software and Modeling Systems Tags , , , , , ,

    The search for a better understanding of complex systems calls for quantitative model development. Within this development process, model fitting to observational data (calibration) often plays an important role. Traditionally, local optimization techniques have been applied to solve nonlinear (as well as linear) model calibration problems numerically: the limitations of such approaches in the nonlinear … Read more

    Three Enhancements for Optimization-Based Bound Tightening

  • Timo Berthold
  • Ambros Gleixner
  • Benjamin Müller
  • Stefan Weltge
    • Categories (Mixed) Integer Nonlinear Programming, Global Optimization, Nonlinear Optimization Tags , , , , ,

    Optimization-based bound tightening (OBBT) is one of the most effective procedures to reduce variable domains of nonconvex mixed-integer nonlinear programs (MINLPs). At the same time it is one of the most expensive bound tightening procedures, since it solves auxiliary linear programs (LPs)—up to twice the number of variables many. The main goal of this paper … Read more

    Optimized Ellipse Packings in Regular Polygons Using Embedded Lagrange Multipliers

  • Ignacio Castillo
  • Frank J. Kampas
  • János Pintér
    • Categories Global Optimization, Global Optimization Applications, Optimization Software and Modeling Systems

    In this work, we present model development and numerical solution approaches to the general problem of packing a collection of ellipses into an optimized regular polygon. Our modeling and solution strategy is based on the concept of embedded Lagrange multipliers. This concept is applicable to a wide range of optimization problems in which explicit analytical … Read more

    Iteration-complexity of a Rockafellar’s proximal method of multipliers for convex programming based on second-order approximations

  • M. Marques Alves
  • Renato D.C. Monteiro
  • Benar Fux Svaiter
    • Categories Constrained Nonlinear Optimization, Convex Optimization, Global Optimization Tags , , , ,

    This paper studies the iteration-complexity of a new primal-dual algorithm based on Rockafellar’s proximal method of multipliers (PMM) for solving smooth convex programming problems with inequality constraints. In each step, either a step of Rockafellar’s PMM for a second-order model of the problem is computed or a relaxed extragradient step is performed. The resulting algorithm … Read more