Linear, Cone and Semidefinite Programming

Solving Stengle’s Example in Rational Arithmetic: Exact Values of the Moment-SOS Relaxations

  • Didier Henrion
    • Categories Semi-definite Programming Tags , , , ,

    We revisit Stengle’s classical univariate polynomial optimization example $\min 1-x^2$ s.t. $(1-x^2)^3\ge 0$ whose constraint description is degenerate at the minimizers. We prove that the moment-SOS hierarchy of relaxation order $r\ge 3$ has the exact value $-1/r(r-2)$. For this we construct in rational arithmetic a dual polynomial sum-of-squares (SOS) certificate and a primal moment sequence … Read more

    Global optimization of low-rank polynomials

  • Llorenç Balada Gaggioli
  • Didier Henrion
  • Milan Korda
    • Categories Global Optimization, Semi-definite Programming

    This work considers polynomial optimization problems where the objective admits a low-rank canonical polyadic tensor decomposition. We introduce LRPOP (low-rank polynomial optimization), a new hierarchy of semidefinite programming relaxations for which the size of the semidefinite blocks is determined by the canonical polyadic rank rather than the number of variables. As a result, LRPOP can … Read more

    Semidefinite hierarchies for diagonal unitary invariant bipartite quantum states

  • Jonas Britz
  • Monique Laurent
    • Categories Semi-definite Programming Tags , , , , , , , , ,

    We investigate questions about the cone \(\mathrm{SEP}_n\) of separable bipartite states, consisting of the Hermitian matrices acting on \(\mathbb{C}^n\otimes\mathbb{C}^n\) that can be written as conic combinations of rank one matrices of the form \(xx^*\otimes yy^*\) with \(x,y\in\mathbb{C}^n\). Bipartite states that are not separable are said to be entangled. Detecting quantum entanglement is a fundamental task … Read more

    Density, Determinacy, Duality and a Regularized Moment-SOS Hierarchy

  • Didier Henrion
    • Categories Linear, Cone and Semidefinite Programming, Semi-definite Programming Tags ,

    The standard moment-sum-of-squares (SOS) hierarchy is a powerful method for solving global polynomial optimization problems. However, its convergence relies on Putinar’s Positivstellensatz, which requires the feasible set to satisfy the algebraic Archimedean property. In this paper, we introduce a regularized moment-SOS hierarchy capable of handling problems on unbounded sets or bounded sets violating the Archimedean … Read more

    A Dual Riemannian ADMM Algorithm for Low-Rank SDPs with Unit Diagonal

  • Jie Wang
    • Categories 0-1 Programming, Semi-definite Programming Tags , , , , , , ,

    This paper proposes a dual Riemannian alternating direction method of multipliers (ADMM) for solving low-rank semidefinite programs with unit diagonal constraints. We recast the ADMM subproblem as a Riemannian optimization problem over the oblique manifold by performing the Burer-Monteiro factorization. Global convergence of the algorithm is established assuming that the subproblem is solved to certain … Read more

    Semidefinite programming via Projective Cutting Planes for dense (easily-feasible) instances

  • Daniel Porumbel
    • Categories Linear, Cone and Semidefinite Programming, Semi-definite Programming Tags , ,

    The cone of positive semi-definite (SDP) matrices can be described by an infinite number of linear constraints. It is well-known that one can optimize over such a feasible area by standard Cutting Planes, but work on this idea remains a rare sight, likely due to its limited practical appeal compared to Interior Point Methods (IPMs). … Read more

    Sparse Multiple Kernel Learning: Alternating Best Response and Semidefinite Relaxations

  • Dimitris Bertsimas
  • Caio de Próspero Iglesias
  • Nicholas A. G. Johnson
    • Categories Convex Optimization, Semi-definite Programming, Statistics Tags , , , ,

    We study Sparse Multiple Kernel Learning (SMKL), which is the problem of selecting a sparse convex combination of prespecified kernels for support vector binary classification. Unlike prevailing \(\ell_1\)‐regularized approaches that approximate a sparsifying penalty, we formulate the problem by imposing an explicit cardinality constraint on the kernel weights and add an \(\ell_2\) penalty for robustness. … Read more

    The SCIP Optimization Suite 10.0

  • Christopher Hojny
  • Mathieu Besançon
  • Ksenia Bestuzheva
  • Sander Borst
  • Antonia Chmiela
  • João Dionísio
  • Leon Eifler
  • Mohammed Ghannam
  • Ambros Gleixner
  • Adrian Göß
  • Alexander Hoen
  • Rolf van der Hulst
  • Dominik Kamp
  • Thorsten Koch
  • Kevin Kofler
  • Jurgen Lentz
  • Stephen J. Maher
  • Gioni Mexi
  • Erik Mühmer
  • Marc E. Pfetsch
  • Sebastian Pokutta
  • Felipe Serrano
  • Yuji Shinano
  • Mark Turner
  • Stefan Vigerske
  • Matthias Walter
  • Dieter Weninger
  • Liding Xu
    • Categories Integer Programming, Linear, Cone and Semidefinite Programming, Optimization Software and Modeling Systems Tags , , , , , , , , ,

    The SCIP Optimization Suite provides a collection of software packages for mathematical optimization, centered around the constraint integer programming (CIP) framework SCIP. This report discusses the enhancements and extensions included in SCIP Optimization Suite 10.0. The updates in SCIP 10.0 include a new solving mode for exactly solving rational mixed-integer linear programs, a new presolver … Read more

    Column Generation for Generalized Min-Cost Flows with Losses

  • Jonas Alker
  • Marc E. Pfetsch
    • Categories Combinatorial Optimization, Linear Programming, Network Optimization Tags ,

    The generalized flow problem deals with flows through a network with losses or gains along the arcs. Motivated by energy networks, this paper concentrates on the case with losses along cycles. Such networks can become extremely large, mostly because they are considered over large time horizons. We therefore develop a column generation approach for a … Read more

    On the Convexification of a Class of Mixed-Integer Conic Sets

  • GuxinDU
  • Rui Chen
  • Linchuan Wei
    • Categories (Mixed) Integer Nonlinear Programming, Cone Programming

    We investigate mixed-integer second-order conic (SOC) sets with a nonlinear right-hand side in the SOC constraint, a structure frequently arising in mixed-integer quadratically constrained programming (MIQCP). Under mild assumptions, we show that the convex hull can be exactly described by replacing the right-hand side with its concave envelope. This characterization enables strong relaxations for MIQCPs … Read more