Linear, Cone and Semidefinite Programming

Maximum Cuts and Fractional Cut Covers: A Computational Study of a Randomized Semidefinite Programming Approach

  • Nathan Benedetto Proença
  • Marcel K. de Carli Silva
  • Levent Tunçel
    • Categories Approximation Algorithms, Optimization Software and Modeling Systems, Semi-definite Programming

    We present experimental work on a primal-dual framework simultaneously approximating maximum cut and weighted fractional cut-covering instances. In this primal-dual framework, we solve a semidefinite programming (SDP) relaxation to either the maximum cut problem or to the weighted fractional cut-covering problem, and then independently sample a collection of cuts via the random-hyperplane technique. We then … Read more

    Finding Short Paths on Simple Polytopes

  • Alexander Black
  • Raphael Steiner
    • Categories Combinatorial Optimization, Linear Programming, Polyhedra Tags , , , , ,

    We prove that computing a shortest monotone path to the optimum of a linear program over a simple polytope is NP-hard, thus resolving a 2022 open question of De Loera, Kafer, and Sanit\`{a}. As a consequence, finding a shortest sequence of pivots to an optimal basis with the simplex method is NP-hard. In fact, we … Read more

    Pricing Discrete and Nonlinear Markets With Semidefinite Relaxations

  • Cheng Guo
  • Lauren Henderson
  • Ryan Cory-Wright
  • Boshi Yang
    • Categories (Mixed) Integer Linear Programming, Applications - OR and Management Sciences, Semi-definite Programming Tags , , , ,

    Nonconvexities in markets with discrete decisions and nonlinear constraints make efficient pricing challenging, often necessitating subsidies. A prime example is the unit commitment (UC) problem in electricity markets, where costly subsidies are commonly required. We propose a new pricing scheme for nonconvex markets with both discreteness and nonlinearity, by convexifying nonconvex structures through a semidefinite … Read more

    On the Single-Multi-Commodity Gap: Lifting Single- to Multicommodity Flow Instances

  • Felix P. Broesamle
  • Stefan Nickel
    • Categories Applications - OR and Management Sciences, Linear Programming, Network Optimization Tags , , , , ,

    Benchmark instances for multicommodity flow problems frequently lack the structural nuances of real-world networks or fail to maintain a rigorous mathematical relationship with their single-commodity counterparts. This paper introduces a formal meta-generation framework that addresses these limitations by lifting single-commodity minimum-cost flow instances into the multicommodity space while strictly preserving the underlying network topology, capacity … Read more

    Separable QCQPs and Their Exact SDP Relaxations

  • Masakazu Kojima
  • Sunyoung Kim
  • Naohiko Arima
    • Categories Global Optimization Theory, Quadratic Programming, Semi-definite Programming Tags , , , , ,

    This paper studies exact semidefinite programming relaxations (SDPRs) for separable quadratically constrained quadratic programs (QCQPs). We consider the construction of a larger separable QCQP from multiple QCQPs with exact SDPRs. We show that exactness is preserved when such QCQPs are combined through a separable horizontal connection, where the coupling is induced through the right-hand-side parameters … Read more

    Beyond binarity: Semidefinite programming for ternary quadratic problems

  • Frank de Meijer
  • Veronica Piccialli
  • Renata Sotirov
  • Antonio M. Sudoso
    • Categories (Mixed) Integer Nonlinear Programming, Quadratic Programming, Semi-definite Programming Tags , , ,

    We study the ternary quadratic problem (TQP), a quadratic optimization problem with linear constraints where the variables take values in {0,±1}. While semidefinite programming (SDP) techniques are well established for {0,1}- and {±1}-valued quadratic problems, no dedicated integer semidefinite programming framework exists for the ternary case. In this paper, we introduce a ternary SDP formulation … Read more

    Modeling Adversarial Wildfires for Power Grid Disruption

  • Matthew Brun
  • Xu Andy Sun
  • Jean-Paul Watson
    • Categories (Mixed) Integer Nonlinear Programming, Energy, Second-Order Cone Programming Tags , , , ,

    Electric power infrastructure faces increasing risk of damage and disruption due to wildfire. Operators of power grids in wildfire-prone regions must consider the potential impacts of unpredictable fires. However, traditional wildfire models do not effectively describe worst-case, or even high-impact, fire behavior. To address this issue, we propose a mixed-integer conic program to characterize an … Read more

    Compact Lifted Relaxations for Low-Rank Optimization

  • Ryan Cory-Wright
  • Jean Pauphilet
    • Categories Semi-definite Programming Tags , ,

    We develop tractable convex relaxations for rank-constrained quadratic optimization problems over $n \times m$ matrices, a setting for which tractable relaxations are typically only available when the objective or constraints admit spectral (permutation-invariant) structure. We derive lifted semidefinite relaxations that do not require such spectral terms. Although a direct lifting introduces a large semidefinite constraint … Read more

    Data-driven Policies For Two-stage Stochastic Linear Programs

  • Chhavi Sharma
  • Harsha Gangammanavar
    • Categories Linear Programming, Optimization in Data Science, Stochastic Programming Tags , , ,

    A stochastic program typically involves several parameters, including deterministic first-stage parameters and stochastic second-stage elements that serve as input data. These programs are re-solved whenever any input parameter changes. However, in practical applications, quick decision-making is necessary, and solving a stochastic program from scratch for every change in input data can be computationally costly. This … Read more

    Folding Mixed-Integer Linear Programs and Reflection Symmetries

  • Rolf van der Hulst
    • Categories (Mixed) Integer Linear Programming, Linear Programming Tags , , , ,

    For mixed-integer linear programming and linear programming it is well known that symmetries can have a negative impact on the performance of branch-and-bound and linear optimization algorithms. A common strategy to handle symmetries in linear programs is to reduce the dimension of the linear program by aggregating symmetric variables and solving a linear program of … Read more