Pierre Bonami

A Classifier to Decide on the Linearization of Mixed-Integer Quadratic Problems in CPLEX

  • Pierre Bonami
  • Andrea Lodi
  • Giulia Zarpellon
    • Categories (Mixed) Integer Linear Programming, Integer Programming, Optimization Software Design Principles Tags , , ,

    We translate the algorithmic question of whether to linearize convex Mixed-Integer Quadratic Programming problems (MIQPs) into a classification task, and use machine learning (ML) techniques to tackle it. We represent MIQPs and the linearization decision by careful target and feature engineering. Computational experiments and evaluation metrics are designed to further incorporate the optimization knowledge in … Read more

    Implementing Automatic Benders Decomposition in a Modern MIP Solver

  • Pierre Bonami
  • Domenico Salvagnin
  • Andrea Tramontani
    • Categories (Mixed) Integer Linear Programming, Cutting Plane Approaches Tags ,

    We describe the automatic Benders decomposition implemented in the commercial solver IBM CPLEX. We propose several improvements to the state-of-the-art along two lines: making a numerically robust method able to deal with the general case and improving the efficiency of the method on models amenable to decomposition. For the former, we deal with: unboundedness, failures … Read more

    Scoring positive semidefinite cutting planes for quadratic optimization via trained neural networks

  • Radu Baltean-Lugojan
  • Pierre Bonami
  • Ruth Misener
  • Andrea Tramontani
    • Categories (Mixed) Integer Nonlinear Programming, Global Optimization, Quadratic Programming Tags , , , , ,

    Semidefinite programming relaxations complement polyhedral relaxations for quadratic optimization, but global optimization solvers built on polyhedral relaxations cannot fully exploit this advantage. This paper develops linear outer-approximations of semidefinite constraints that can be effectively integrated into global solvers. The difference from previous work is that our proposed cuts are (i) sparser with respect to the … Read more

    Solving Box-Constrained Nonconvex Quadratic Programs

  • Pierre Bonami
  • Oktay Gunluk
  • Jeff Linderoth
    • Categories Quadratic Programming

    We present effective computational techniques for solving nonconvex quadratic programs with box constraints (BoxQP). We first observe that cutting planes obtained from the Boolean Quadric Polytope (BQP) are computationally effective at reducing the optimality gap of BoxQP. We next show that the Chvatal-Gomory closure of the BQP is given by the odd-cycle inequalities even when … Read more

    A Note on Linear On/Off Constraints

  • Pierre Bonami
  • Hassan L. Hijazi
  • Adam Ouorou
    • Categories (Mixed) Integer Linear Programming, Polyhedra Tags ,

    This note studies compact representations of linear on/off constraints in mixed-integer linear optimization. A characterization of the convex hull of linear disjunctions is given in the space of original variables. This result can improve formulations of mixed-integer linear programs featuring on/off constraints by reducing the integrality gap in a Branch and Bound approach. Citation@article{, year={2014}, … Read more

    An Outer-Inner Approximation for separable MINLPs

  • Pierre Bonami
  • Hassan L. Hijazi
  • Adam Ouorou
    • Categories (Mixed) Integer Nonlinear Programming, Optimization Software and Modeling Systems Tags , ,

    A common structure in convex mixed-integer nonlinear programs is separable nonlinear functions. In the presence of such structures, we propose three improvements to the outer approximation algorithms. The first improvement is a simple extended formulation, the second is a refined outer approximation, and the third is a heuristic inner approximation of the feasible region. These … Read more

    More Branch-and-Bound Experiments in Convex Nonlinear Integer Programming

  • Pierre Bonami
  • Jon Lee
  • Sven Leyffer
  • Andreas Wächter
    • Categories (Mixed) Integer Nonlinear Programming

    Branch-and-Bound (B&B) is perhaps the most fundamental algorithm for the global solution of convex Mixed-Integer Nonlinear Programming (MINLP) problems. It is well-known that carrying out branching in a non-simplistic manner can greatly enhance the practicality of B&B in the context of Mixed-Integer Linear Programming (MILP). No detailed study of branching has heretofore been carried out … Read more

    An Outer-Inner Approximation for separable MINLPs

  • Pierre Bonami
  • Hassan L. Hijazi
  • Adam Ouorou
    • Categories (Mixed) Integer Nonlinear Programming Tags ,

    A common structure in convex mixed-integer nonlinear programs is additively separable nonlinear functions consisting of a sum of univariate functions. In the presence of such structures, we propose three improvements to the classical Outer Approximation algorithms that exploit separability. The first improvement is a simple extended formulation. The second a refined outer approximation. Finally, the … Read more

    On optimizing over lift-and-project closures

  • Pierre Bonami
    • Categories (Mixed) Integer Linear Programming

    The lift-and-project closure is the relaxation obtained by computing all lift-and-project cuts from the initial formulation of a mixed integer linear program or equivalently by computing all mixed integer Gomory cuts read from all tableau’s corresponding to feasible and infeasible bases. In this paper, we present an algorithm for approximating the value of the lift-and-project … Read more

    Mixed Integer NonLinear Programs featuring “On/Off ” constraints: convex analysis and applications

  • Pierre Bonami
  • Gérard Cornuéjols
  • Hassan L. Hijazi
  • Adam Ouorou
    • Categories (Mixed) Integer Nonlinear Programming

    We call ”on/off” constraint an algebraic constraint that is activated if and only if a corresponding boolean variable is turned ”on” or equal to 1. Our main subject of interest is to derive tight convex formulations of Mixed Integer NonLinear Programs (MINLPs) featuring ”on/off” constraints. We study the simple set defined by one ”on/off” constraint … Read more