Quadratic Programming

QCQP with Extra Constant Modulus Constraints: Theory and Applications on QoS Constrained Hybrid Beamforming for mmWave MU-MIMO

  • Xin He
    • Categories Constrained Nonlinear Optimization, Quadratic Programming, Telecommunications Tags , , , , , , , ,

    The constant modulus constraint is widely used in analog beamforming, hybrid beamforming, intelligent reflecting surface design, and radar waveform design. The quadratically constrained quadratic programming (QCQP) problem is also widely used in signal processing. However, the QCQP with extra constant modulus constraints was not systematically studied in mathematic programming and signal processing. For example, the … Read more

    Generating Cutting Inequalities Successively for Quadratic Optimization Problems in Binary Variables

  • Sunyoung Kim
  • Masakazu Kojima
    • Categories 0-1 Programming, Linear, Cone and Semidefinite Programming, Quadratic Programming Tags , , , , , , ,

    We propose a successive generation of cutting inequalities for binary quadratic optimization problems. Multiple cutting inequalities are successively generated for the convex hull of the set of the optimal solutions $\subset \{0, 1\}^n$, while the standard cutting inequalities are used for the convex hull of the feasible region. An arbitrary linear inequality with integer coefficients … Read more

    Inductive Linearization for Binary Quadratic Programs with Linear Constraints: A Computational Study

  • Sven Mallach
    • Categories (Mixed) Integer Nonlinear Programming, 0-1 Programming, Quadratic Programming Tags , , ,

    The computational performance of inductive linearizations for binary quadratic programs in combination with a mixed-integer programming solver is investigated for several combinatorial optimization problems and established benchmark instances. Apparently, a few of these are solved to optimality for the first time. Citationpreprint (no internal series / number): University of Bonn, Germany June 11, 2021ArticleDownload View … 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

    SOS-SDP: an Exact Solver for Minimum Sum-of-Squares Clustering

  • Veronica Piccialli
  • Antonio M. Sudoso
  • Angelika Wiegele
    • Categories 0-1 Programming, Quadratic Programming, Semi-definite Programming

    The minimum sum-of-squares clustering problem (MSSC) consists in partitioning n observations into k clusters in order to minimize the sum of squared distances from the points to the centroid of their cluster. In this paper, we propose an exact algorithm for the MSSC problem based on the branch-and-bound technique. The lower bound is computed by … Read more

    Cutting Plane Generation Through Sparse Principal Component Analysis

  • Santanu S. Dey
  • Aleksandr M. Kazachkov
  • Andrea Lodi
  • Gonzalo Muñoz
    • Categories Cutting Plane Approaches, Quadratic Programming Tags , , ,

    Quadratically-constrained quadratic programs (QCQPs) are optimization models whose remarkable expressiveness has made them a cornerstone of methodological research for nonconvex optimization problems. However, modern methods to solve a general QCQP fail to scale, encountering computational challenges even with just a few hundred variables. Specifically, a semidefinite programming (SDP) relaxation is typically employed, which provides strong … Read more

    New notions of simultaneous diagonalizability of quadratic forms with applications to QCQPs

  • Rujun Jiang
  • Alex L. Wang
    • Categories Quadratic Programming Tags , , , ,

    A set of quadratic forms is simultaneously diagonalizable via congruence (SDC) if there exists a basis under which each of the quadratic forms is diagonal. This property appears naturally when analyzing quadratically constrained quadratic programs (QCQPs) and has important implications in this context. This paper extends the reach of the SDC property by studying two … Read more

    Supermodularity and valid inequalities for quadratic optimization with indicators

  • Alper Atamturk
  • Andrés Gómez
    • Categories (Mixed) Integer Nonlinear Programming, Quadratic Programming Tags , , , , ,

    We study the minimization of a rank-one quadratic with indicators and show that the underlying set function obtained by projecting out the continuous variables is supermodular. Although supermodular minimization is, in general, difficult, the specific set function for the rank-one quadratic can be minimized in linear time. We show that the convex hull of the … Read more

    ADMM and inexact ALM: the QP case

  • Stefano Cipolla
  • Jacek Gondzio
    • Categories Quadratic Programming Tags , ,

    Embedding randomization procedures in the Alternating Direction Method of Multipliers (ADMM) has recently attracted an increasing amount of interest as a remedy to the fact that the direct n-block generalization of ADMM is not necessarily convergent ($n \geq 3$). Even if, in practice, the introduction of such techniques could mitigate the diverging behaviour of the … Read more

    EFIX: Exact Fixed Point Methods for Distributed Optimization

  • Dušan Jakovetić
  • Nataša Krejić
  • Nataša Krklec Jerinkić
    • Categories Convex Optimization, Global Optimization Theory, Quadratic Programming Tags , , ,

    We consider strongly convex distributed consensus optimization over connected networks. EFIX, the proposed method, is derived using quadratic penalty approach. In more detail, we use the standard reformulation – transforming the original problem into a constrained problem in a higher dimensional space – to define a sequence of suitable quadratic penalty subproblems with increasing penalty … Read more