Global Optimization

On Piecewise Linear Approximations of Bilinear Terms: Structural Comparison of Univariate and Bivariate Mixed-Integer Programming Formulations

  • Lukas Hager
  • Robert Burlacu
  • Andreas Bärmann
  • Thomas Kleinert
    • Categories (Mixed) Integer Linear Programming, Global Optimization Theory, Quadratic Programming Tags , , , ,

    Bilinear terms naturally appear in many optimization problems. Their inherent nonconvexity typically makes them challenging to solve. One approach to tackle this difficulty is to use bivariate piecewise linear approximations for each variable product, which can be represented via mixed-integer linear programming (MIP) formulations. Alternatively, one can reformulate the variable products as a sum of … Read more

    A Reformulation Technique to Solve Polynomial Optimization Problems with Separable Objective Functions of Bounded Integer Variables

  • Andrew C. Trapp
  • Pitchaya Wiratchotisatian
    • Categories (Mixed) Integer Nonlinear Programming, Global Optimization Theory, Nonlinear Optimization Tags , , ,

    Real-world problems are often nonconvex and involve integer variables, representing vexing challenges to be tackled using state-of-the-art solvers. We introduce a mathematical identity-based reformulation of a class of polynomial integer nonlinear optimization (PINLO) problems using a technique that linearizes polynomial functions of separable and bounded integer variables of any degree. We also introduce an alternative … Read more

    Global Optimization for Nonconvex Programs via Convex Proximal Point Method

  • Wenxun Xing
  • Yuanyi Zhao
    • Categories Applications - OR and Management Sciences, Global Optimization

    The nonconvex program plays an important role in the field of optimization and has a lot of applications in practice. However, for general nonconvex programming problems, the lack of verifiable global optimal conditions and the multiple local minimizers make global optimization hard in computation. In this paper, a convex proximal point algorithm (CPPA) is considered … Read more

    Global optimization using random embeddings

  • Coralia Cartis
  • Estelle Massart
  • Adilet Otemissov
    • Categories Global Optimization, Nonlinear Optimization Tags , , , ,

    We propose a random-subspace algorithmic framework for global optimization of Lipschitz-continuous objectives, and analyse its convergence using novel tools from conic integral geometry. X-REGO randomly projects, in a sequential or simultaneous manner, the high- dimensional original problem into low-dimensional subproblems that can then be solved with any global, or even local, optimization solver. We estimate … Read more

    Exactness in SDP relaxations of QCQPs: Theory and applications

  • Fatma Kılınç-Karzan
  • Alex L. Wang
    • Categories Global Optimization Theory, Semi-definite Programming

    Quadratically constrained quadratic programs (QCQPs) are a fundamental class of optimization problems. In a QCQP, we are asked to minimize a (possibly nonconvex) quadratic function subject to a number of (possibly nonconvex) quadratic constraints. Such problems arise naturally in many areas of operations research, computer science, and engineering. Although QCQPs are NP-hard to solve in … Read more

    The Promise of EV-Aware Multi-Period OPF Problem: Cost and Emission Benefits

  • Sezen Ece Kayacık
  • Burak Kocuk
  • Tuğçe Yüksel
    • Categories Applications - OR and Management Sciences, Global Optimization, Second-Order Cone Programming Tags , ,

    In this paper, we study the Multi-Period Optimal Power Flow problem (MOPF) with electric vehicles (EV) under emission considerations. We integrate three different real-world datasets: household electricity consumption, marginal emission factors, and EV driving profiles. We present a systematic solution approach based on second-order cone programming to find globally optimal solutions for the resulting nonconvex … Read more

    An extension of the Reformulation-Linearization Technique to nonlinear optimization

  • Danique de Moor
  • Dick den Hertog
  • Jianzhe Zhen
    • Categories Constrained Nonlinear Optimization, Global Optimization Tags , , ,

    We introduce a novel Reformulation-Perspectification Technique (RPT) to obtain convex approximations of nonconvex continuous optimization problems. RPT consists of two steps, those are, a reformulation step and a perspectification step. The reformulation step generates redundant nonconvex constraints from pairwise multiplication of the existing constraints. The perspectification step then convexifies the nonconvex components by using perspective … Read more

    SDP-quality bounds via convex quadratic relaxations for global optimization of mixed-integer quadratic programs

  • Carlos Nohra
  • Arvind U. Raghunathan
  • Nikolaos Sahinidis
    • Categories (Mixed) Integer Nonlinear Programming, Global Optimization Tags , , , ,

    We consider the global optimization of nonconvex mixed-integer quadratic programs with linear equality constraints. In particular, we present a new class of convex quadratic relaxations which are derived via quadratic cuts. To construct these quadratic cuts, we solve a separation problem involving a linear matrix inequality with a special structure that allows the use of … Read more

    On obtaining the convex hull of quadratic inequalities via aggregations

  • Santanu S. Dey
  • Felipe Serrano
  • Gonzalo Muñoz
    • Categories Global Optimization Theory Tags , ,

    A classical approach for obtaining valid inequalities for a set involves weighted aggregations of the inequalities that describe such set. When the set is described by linear inequalities, thanks to the Farkas lemma, we know that every valid inequality can be obtained using aggregations. When the inequalities describing the set are two quadratics, Yildiran showed … Read more

    MatQapNB User Guide: A branch-and-bound program for QAPs in Matlab with the Newton-Bracketing method

  • Koichi Fujii
  • Naoki Ito
  • Sunyoung Kim
  • Masakazu Kojima
  • Hans D Mittelmann
  • Kim-Chuan Toh
  • Yuji Shinano
    • Categories Global Optimization Applications, Optimization Software Design Principles, Quadratic Programming Tags , , ,

    MatQapNB is a MATLAB toolbox that implements a parallel branch-and-bound method using NewtBracket (the Newton bracketing method [4]) for its lower bounding procedure. It can solve small to medium scale Quadratic Assignment Problem (QAP) instances with dimension up to 30. MatQapNB was used in the numerical experiments on QAPs in the recent article “Solving challenging … Read more