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The random greedy algorithm for finding a maximal independent set in a graph constructs a maximal independent set by inspecting the graph's vertices in a random order, adding the current vertex to the independent set if it is not adjacent…

Combinatorics · Mathematics 2023-09-28 Michael Krivelevich , Tamás Mészáros , Peleg Michaeli , Clara Shikhelman

In this paper, we consider a randomized greedy algorithm for independent sets in $r$-uniform $d$-regular hypergraphs $G$ on $n$ vertices with girth $g$. By analyzing the expected size of the independent sets generated by this algorithm, we…

Combinatorics · Mathematics 2022-01-06 Jiaxi Nie , Jacques Verstraete

Let $r\ge 3$ be a fixed constant and let $ {\mathcal H}$ be an $r$-uniform, $D$-regular hypergraph on $N$ vertices. Assume further that $ D > N^\varepsilon $ for some $ \varepsilon>0 $. Consider the random greedy algorithm for forming an…

Combinatorics · Mathematics 2024-09-25 Patrick Bennett , Tom Bohman

We derive new results for the performance of a simple greedy algorithm for finding large independent sets and matchings in constant degree regular graphs. We show that for $r$-regular graphs with $n$ nodes and girth at least $g$, the…

Discrete Mathematics · Computer Science 2008-07-09 David Gamarnik , David Goldberg

We study the greedy independent set algorithm on sparse Erd\H{o}s-R\'enyi random graphs ${\mathcal G}(n,c/n)$. This range of $p$ is of interest due to the threshold at $c=e$, beyond which it appears that greedy algorithms are affected by a…

Probability · Mathematics 2025-11-18 Brett Kolesnik

Computing the size of maximum independent sets is a NP-hard problem for fixed graphs. Characterizing and designing efficient algorithms to estimate this independence number for random graphs are notoriously difficult and still largely open…

Probability · Mathematics 2020-10-01 Paola Bermolen , Matthieu Jonckheere , Federico Larroca , Manuel Saenz

In this thesis, which is supervised by Dr. David Penman, we examine random interval graphs. Recall that such a graph is defined by letting $X_{1},\ldots X_{n},Y_{1},\ldots Y_{n}$ be $2n$ independent random variables, with uniform…

Combinatorics · Mathematics 2019-05-27 Vasileios Iliopoulos

We consider numbers and sizes of independent sets in graphs with minimum degree at least $d$, when the number $n$ of vertices is large. In particular we investigate which of these graphs yield the maximum numbers of independent sets of…

Combinatorics · Mathematics 2012-10-05 Hiu-Fai Law , Colin McDiarmid

We prove new lower bounds on the likely size of a maximum independent set in a random graph with a given average degree. Our method is a weighted version of the second moment method, where we give each independent set a weight based on the…

Computational Complexity · Computer Science 2011-11-15 Varsha Dani , Cristopher Moore

In this article we prove that the minimum-degree greedy algorithm, with adversarial tie-breaking, is a $(2/3)$-approximation for the Maximum Independent Set problem on interval graphs. We show that this is tight, even on unit interval…

Data Structures and Algorithms · Computer Science 2024-03-19 Steven Chaplick , Martin Frohn , Steven Kelk , Johann Lottermoser , Matus Mihalak

This paper presents a linear prioritized local algorithm that computes large independent sets on a random $d$-regular graph with small and fixed degree $d$. We studied experimentally the independence ratio obtained by the algorithm when $ d…

Data Structures and Algorithms · Computer Science 2021-08-18 Raffaele Marino , Scott Kirkpatrick

We study the approximability of the maximum size independent set (MIS) problem in bounded degree graphs. This is one of the most classic and widely studied NP-hard optimization problems. We focus on the well known minimum degree greedy…

Data Structures and Algorithms · Computer Science 2020-02-03 Piotr Krysta , Mathieu Mari , Nan Zhi

Let $X_1,X_2,...$ be an infinite sequence of i.i.d. random vectors distributed exponentially with parameter $\lam .$ For each $y$ and $n\geq 1,$ form a graph $G_n(y)$ with vertex set $V_n = \{X_1,...,X_n\},$ two vertices are connected if…

Probability · Mathematics 2007-05-23 Bhupendra Gupta

We consider a class of growing random graphs obtained by creating vertices sequentially one by one: at each step, we choose uniformly the neighbours of the newly created vertex; its degree is a random variable with a fixed but arbitrary…

Combinatorics · Mathematics 2013-11-13 Svante Janson , Simone Severini

Finding independent sets of maximum size in fixed graphs is well known to be an NP-hard task. Using scaling limits, we characterise the asymptotics of sequential degree-greedy explorations and provide sufficient conditions for this…

Probability · Mathematics 2019-01-04 Matthieu Jonckheere , Manuel Sáenz

We consider the set of all graphs on n labeled vertices with prescribed degrees D=(d_1, ..., d_n). For a wide class of tame degree sequences D we prove a computationally efficient asymptotic formula approximating the number of graphs within…

Combinatorics · Mathematics 2011-12-05 Alexander Barvinok , J. A. Hartigan

In this note, we analyze two random greedy processes on sparse random graphs and hypergraphs with a given degree sequence. First we analyze the matching process, which builds a set of disjoint edges one edge at a time; then we analyze the…

Combinatorics · Mathematics 2021-09-24 Deepak Bal , Patrick Bennett

In this paper, we develop efficient exact and approximate algorithms for computing a maximum independent set in random graphs. In a random graph $G$, each pair of vertices are joined by an edge with a probability $p$, where $p$ is a…

Data Structures and Algorithms · Computer Science 2013-08-08 Yinglei Song

The greedy algorithm A iterates over a set of uniformly sized independent sets of a given graph G and checks for each set S which non-neighbor of S, if any, is best suited to be added to S, until no more suitable non-neighbors are found for…

Data Structures and Algorithms · Computer Science 2015-05-05 Asbjørn Brændeland

We analyze a minimal model of a growing network. At each time step, a new vertex is added; then, with probability delta, two vertices are chosen uniformly at random and joined by an undirected edge. This process is repeated for t time…

Statistical Mechanics · Physics 2009-11-07 Duncan S. Callaway , John E. Hopcroft , Jon M. Kleinberg , M. E. J. Newman , Steven H. Strogatz
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