computation

Recycling Valid Inequalities for Robust Combinatorial Optimization with Budget Uncertainty

  • Christina Büsing
  • Timo Gersing
  • Arie M.C.A. Koster
    • Categories 0-1 Programming, Polyhedra, Robust Optimization Tags , , , ,

    Robust combinatorial optimization with budget uncertainty is one of the most popular approaches for integrating uncertainty into optimization problems. The existence of a compact reformulation for (mixed-integer) linear programs and positive complexity results give the impression that these problems are relatively easy to solve. However, the practical performance of the reformulation is quite poor when … Read more

    Balancing Communication and Computation in Gradient Tracking Algorithms for Decentralized Optimization

  • Albert S. Berahas
  • Raghu Bollapragada
  • Shagun Gupta
    • Categories Convex Optimization, Nonlinear Optimization, Optimization in Data Science Tags , , , ,

    Gradient tracking methods have emerged as one of the most popular approaches for solving decentralized optimization problems over networks. In this setting, each node in the network has a portion of the global objective function, and the goal is to collectively optimize this function. At every iteration, gradient tracking methods perform two operations (steps): (1) … Read more

    A Branch & Bound Algorithm for Robust Binary Optimization with Budget Uncertainty

  • Christina Büsing
  • Timo Gersing
  • Arie M.C.A. Koster
    • Categories 0-1 Programming, Branch and Cut Algorithms, Robust Optimization Tags , , , ,

    Since its introduction in the early 2000s, robust optimization with budget uncertainty has received a lot of attention. This is due to the intuitive construction of the uncertainty sets and the existence of a compact robust reformulation for (mixed-integer) linear programs. However, despite its compactness, the reformulation performs poorly when solving robust integer problems due … Read more

    Balancing Communication and Computation in Distributed Optimization

  • Albert S. Berahas
  • Raghu Bollapragada
  • Nitish Shirish Keskar
  • Ermin Wei
    • Categories Convex Optimization, Distributed Control, Network Optimization Tags , , , ,

    Methods for distributed optimization have received significant attention in recent years owing to their wide applicability in various domains including machine learning, robotics and sensor networks. A distributed optimization method typically consists of two key components: communication and computation. More specifically, at every iteration (or every several iterations) of a distributed algorithm, each node in … Read more

    Computation of Graphical Derivative for a Class of Normal Cone Mappings under a Very Weak Condition

  • Huy Chieu Nguyen
  • Le Van Hien
    • Categories Nonsmooth Optimization Tags , , , ,

    Let $\Gamma:=\{x\in \R^n\, |\, q(x)\in\Theta\},$ where $q: \R^n\rightarrow\R^m$ is a twice continuously differentiable mapping, and $\Theta$ is a nonempty polyhedral convex set in $\R^m.$ In this paper, we first establish a formula for exactly computing the graphical derivative of the normal cone mapping $N_\Gamma:\R^n\rightrightarrows\R^n,$ $x\mapsto N_\Gamma(x),$ under the condition that $M_q(x):=q(x)-\Theta$ is metrically subregular at … Read more

    Gas Network Optimization: A comparison of Piecewise Linear Models

  • Carlos M. Correa-Posada
  • Pedro Sanchez-Martan
    • Categories (Mixed) Integer Linear Programming, Chemical Engineering Tags , , , , ,

    Gas network optimization manages the gas transport by minimizing operating costs and fulfilling contracts between consumers and suppliers. This is an NP- hard problem governed by non-convex and nonlinear gas transport functions that can be modeled by mixed integer linear programming (MILP) techniques. Under these methods, piecewise linear functions describe nonlinearities and bi- nary variables … Read more

    On Mixing Sets Arising in Chance-Constrained Programming

  • Simge Küçükyavuz
    • Categories (Mixed) Integer Linear Programming, Stochastic Programming Tags , , , , ,

    The mixing set with a knapsack constraint arises in deterministic equivalent of probabilistic programming problems with finite discrete distributions. We first consider the case that the probabilistic program has equal probabilities for each scenario. We study the resulting mixing set with a cardinality constraint and propose facet-defining inequalities that subsume known explicit inequalities for this … Read more

    Uncapacitated Lot Sizing with Backlogging: The Convex Hull

  • Simge Küçükyavuz
  • Yves Pochet
    • Categories Applications - OR and Management Sciences, Cutting Plane Approaches, Polyhedra Tags , , , ,

    An explicit description of the convex hull of solutions to the uncapacitated lot-sizing problem with backlogging, in its natural space of production, setup, inventory and backlogging variables, has been an open question for many years. In this paper, we identify facet-defining inequalities that subsume all previously known valid inequalities for this problem. We show that … Read more

    Lot Sizing with Inventory Bounds and Fixed Costs: Polyhedral Study and Computation

  • Alper Atamturk
  • Simge Küçükyavuz
    • Categories Cutting Plane Approaches, Production and Logistics Tags , , ,

    We investigate the polyhedral structure of the lot-sizing problem with inventory bounds. We consider two models, one with linear costs on inventory, the other with linear and fixed costs on inventory. For both models, we identify facet-defining inequalities that make use of the inventory capacities explicitly and give exact separation algorithms. We also give a … Read more

    A Branch-and-Price Algorithm and New Test Problems for Spectrum Auctions

  • Sven de Vries
  • Oktay Gunluk
  • Lazslo Ladanyi
    • Categories Applications - OR and Management Sciences, Integer Programming Tags , , ,

    When combinatorial bidding is permitted in Spectrum Auctions, such as the upcoming FCC auction #31, the resulting winner-determination problem can be computationally challenging. We present a branch-and-price algorithm based on a set-packing formulation originally proposed by Dietrich and Forrest (2002). This formulation has a variable for every possible combination of winning bids for each bidder. … Read more