Search

A vector is dyadic if each of its entries is a dyadic rational number, i.e. of the form a 2 k for some integers a, k with k ≥ 0 . A linear system A x ≤ b with integral data is totally dual dyadic if whenever min { b ⊤ y : A ⊤ y = w , y ≥ 0 } for w integral, has an optimal solution, it has a dyadic optimal solution. In this paper, we study total dual dyadicness, and give a co-NP characterization of it in terms of dyadic generating sets for cones and subspaces, the former being the dyadic analogue of Hilbert bases, and the latter a polynomial-time recognizable relaxation of the former. Along the way, we see some surprising turn of events when compared to total dual integrality, primarily led by the density of the dyadic rationals. Our study ultimately leads to a better understanding of total dual integrality and polyhedral integrality. We see examples from dyadic matroids, T-joins, cycles, and perfect matchings of a graph. [ABSTRACT FROM AUTHOR]

Even-cycle matroids are elementary lifts of graphic matroids. An even-cycle matroid is pinch-graphic if it has a signed-graph representation with a blocking pair. We present a polynomial algorithm to check if an internally 4-connected binary matroid is pinch-graphic. Combining this with a result in Guenin and Heo (Small separations in pinch-graphic matroids. Math Program (2023). https://doi.org/10.1007/s10107-023-01950-8) this allows us to check, in polynomial time, if an arbitrary binary matroid is pinch-graphic. [ABSTRACT FROM AUTHOR]

Even-cycle matroids are elementary lifts of graphic matroids. Pinch-graphic matroids are even-cycle matroids that are also elementary projections of graphic matroids. In this paper we analyze the structure of 1-, 2-, and 3-separations in these matroids. As a corollary we obtain a polynomial-time algorithm that reduces the problem of recognizing pinch-graphic matroids to internally 4-connected matroids. Combining this with earlier results (Guenin and Heo in Recognizing even-cycle and even-cut matroids manuscript, 2020; Guenin and Heo in Recognizing pinch-graphic matroids manuscript, 2020) we obtain a polynomial-time algorithm for recognizing even-cycle matroids and we obtain a polynomial-time algorithm for recognizing even-cut matroids. [ABSTRACT FROM AUTHOR]

Even-cycle matroids are elementary lifts of graphic matroids and even-cut matroids are elementary lifts of cographic matroids. We present a polynomial algorithm to check if a binary matroid is an even-cycle matroid and we present a polynomial algorithm to check if a binary matroid is an even-cut matroid. These two algorithms rely on a polynomial algorithm (to be described in a pair of follow-up papers) to check if a binary matroid is pinch-graphic. [ABSTRACT FROM AUTHOR]

We compare the relative strength of valid inequalities for the integer hull of the feasible region of mixed integer linear programs with two equality constraints, two unrestricted integer variables and any number of nonnegative continuous variables. In particular, we prove that the closure of Type 2 triangle (resp. Type 3 triangle; quadrilateral) inequalities, are all within a factor of $$1.5$$ of the integer hull, and provide examples showing that the approximation factor is not less than $$1.125$$ . There is no fixed approximation ratio for split or Type 1 triangle inequalities however. [ABSTRACT FROM AUTHOR]

A rational number is dyadic if it has a finite binary representation p/2k\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$p/2^k$$\end{document}, where p is an integer and k is a nonnegative integer. Dyadic rationals are important for numerical computations because they have an exact representation in floating-point arithmetic on a computer. A vector is dyadic if all its entries are dyadic rationals. We study the problem of finding a dyadic optimal solution to a linear program, if one exists. We show how to solve dyadic linear programs in polynomial time. We give bounds on the size of the support of a solution as well as on the size of the denominators. We identify properties that make the solution of dyadic linear programs possible: closure under addition and negation, and density, and we extend the algorithmic framework beyond the dyadic case. [ABSTRACT FROM AUTHOR]