Christoph Buchheim

A Fast Branch-and-Bound Algorithm for Non-convex Quadratic Integer Optimization Subject To Linear Constraints Using Ellipsoidal Relaxations

  • Christoph Buchheim
  • Marianna De Santis
  • Laura Palagi
    • Categories (Mixed) Integer Nonlinear Programming, Global Optimization, Quadratic Programming

    We propose two exact approaches for non-convex quadratic integer minimization subject to linear constraints where lower bounds are computed by considering ellipsoidal relaxations of the feasible set. In the first approach, we intersect the ellipsoids with the feasible linear subspace. In the second approach we penalize exactly the linear constraints. We investigate the connection between … Read more

    On the Quadratic Shortest Path Problem

  • Christoph Buchheim
  • Federico Malucelli
  • Borzou Rostami
  • Davide Frey
    • Categories Combinatorial Optimization, Quadratic Programming Tags , ,

    Finding the shortest path in a directed graph is one of the most important combinatorial optimization problems, having applications in a wide range of fields. In its basic version, however, the problem fails to represent situations in which the value of the objective function is determined not only by the choice of each single arc, … Read more

    Lower Bounding Procedures for the Single Allocation Hub Location Problem

  • Christoph Buchheim
  • Uwe Clausen
  • J. Fabian Meier
  • Borzou Rostami
    • Categories 0-1 Programming, Graphs and Matroids, Production and Logistics Tags , ,

    This paper proposes a new lower bounding procedure for the Uncapacitated Single Allocation p-Hub Median Problem based on Lagrangean relaxation. For solving the resulting Lagrangean subproblem, the given problem structure is exploited: it can be decomposed into smaller subproblems that can be solved efficiently by combinatorial algorithms. Our computational experiments for some benchmark instances demonstrate … Read more

    A Compact Linearisation of Euclidean Single Allocation Hub Location Problems

  • Christoph Buchheim
  • Uwe Clausen
  • J. Fabian Meier
  • Borzou Rostami
    • Categories 0-1 Programming, Network Optimization, Production and Logistics Tags , ,

    Hub location problems are strategic network planning problems. They formalise the challenge of mutually exchanging shipments between a large set of depots. The aim is to choose a set of hubs (out of a given set of possible hubs) and connect every depot to a hub so that the total transport costs for exchanging shipments … Read more

    Min-max-min robustness: a new approach to combinatorial optimization under uncertainty based on multiple solutions

  • Christoph Buchheim
  • Jannis Kurtz
    • Categories Combinatorial Optimization, Integer Programming, Robust Optimization

    In the classical min-max approach to robust combinatorial optimization, a single feasible solution is computed that optimizes the worst case over a given set of considered scenarios. As is well known, this approach is very conservative, leading to solutions that in the average case are far from being optimal. In this paper, we present a … Read more

    A Lagrangean Decomposition Approach for Robust Combinatorial Optimization

  • Frank Baumann
  • Christoph Buchheim
  • Anna Ilyina
    • Categories Combinatorial Optimization, Constrained Nonlinear Optimization, Robust Optimization Tags , , ,

    We address robust versions of combinatorial optimization problems, specializing on the discrete scenario case and the uncorrelated ellipsoidal uncertainty case. We present a branch and bound-algorithm for the min-max variant of these problems which uses lower bounds obtained from Lagrangean decomposition, allowing to separate the uncertainty aspect in the objective function from the combinatorial structure … Read more

    A Feasible Active Set Method with Reoptimization for Convex Quadratic Mixed-Integer Programming

  • Christoph Buchheim
  • Marianna De Santis
  • Stefano Lucidi
  • Francesco Rinaldi
  • Long Trieu
    • Categories (Mixed) Integer Nonlinear Programming, Quadratic Programming Tags , ,

    We propose a feasible active set method for convex quadratic programming problems with non-negativity constraints. This method is specifically designed to be embedded into a branch-and-bound algorithm for convex quadratic mixed integer programming problems. The branch-and-bound algorithm generalizes the approach for unconstrained convex quadratic integer programming proposed by Buchheim, Caprara and Lodi to the presence … Read more

    Lagrangean Decomposition for Mean-Variance Combinatorial Optimization

  • Frank Baumann
  • Christoph Buchheim
  • Anna Ilyina
    • Categories Combinatorial Optimization, Constrained Nonlinear Optimization, Robust Optimization Tags , ,

    We address robust versions of combinatorial optimization problems, focusing on the uncorrelated ellipsoidal uncertainty case, which corresponds to so-called mean-variance optimization. We present a branch and bound-algorithm for such problems that uses lower bounds obtained from Lagrangean decomposition. This approach allows to separate the uncertainty aspect in the objective function from the combinatorial structure of … Read more

    Active Set Methods with Reoptimization for Convex Quadratic Integer Programming

  • Christoph Buchheim
  • Long Trieu
    • Categories (Mixed) Integer Nonlinear Programming, Convex Optimization, Quadratic Programming Tags , ,

    We present a fast branch-and-bound algorithm for solving convex quadratic integer programs with few linear constraints. In each node, we solve the dual problem of the continuous relaxation using an infeasible active set method proposed by Kunisch and Rendl to get a lower bound; this active set algorithm is well suited for reoptimization. Our algorithm … Read more

    Monomial-wise Optimal Separable Underestimators for Mixed-Integer Polynomial Optimization

  • Christoph Buchheim
  • Claudia D'Ambrosio
    • Categories (Mixed) Integer Nonlinear Programming, Bound-constrained Optimization, Global Optimization

    In this paper we introduce a new method for solving box-constrained mixed-integer polynomial problems to global optimality. The approach, a specialized branch-and-bound algorithm, is based on the computation of lower bounds provided by the minimization of separable underestimators of the polynomial objective function. The underestimators are the novelty of the approach because the standard approaches … Read more