scholarly journals On star family packing of graphs

Author(s):  
Mengya Li ◽  
Wensong Lin

Let $\mathcal{H}$ be a family of graphs. An $\mathcal{H}$-packing of a graph $G$ is a set $\{G_1,G_2,\dots,G_k\}$ of disjoint subgraphs of $G$ such that each $G_j$ is isomorphic to some element of $\mathcal{H}$. An $\mathcal{H}$-packing of a graph $G$ that covers the maximum number of vertices of $G$ is called a maximum $\mathcal{H}$-packing of $G$. The $\mathcal{H}$-packing problem seeks to find a maximum $\mathcal{H}$-packing of a graph. Let $i$ be a positive integer. An $i$-star is a complete bipartite graph $K_{1,i}$. This paper investigates the $\mathcal{H}$-packing problem with $\mathcal{H}$ being a family of stars. For an arbitrary family $\mathcal{S}$ of stars, we design a linear-time algorithm for the $\mathcal{S}$-packing problem in trees. Let $t$ be a positive integer. An $\mathcal{H}$-packing is called a $t^+$-star packing if $\mathcal{H}$ consists of all $i$-stars with $i\ge t$. We show that the $t^+$-star packing problem for $t\ge 2$ is NP-hard in bipartite graphs. As a consequence, the $2^+$-star packing problem is NP-hard even in bipartite graphs with maximum degree at most $4$. Let $T$ and $t$ be two positive integers with $T>t$. An $\mathcal{H}$-packing is called a $T\setminus t$-star packing if $\mathcal{H}=\{K_{1,1},K_{1,2},\dots,K_{1,T}\}\setminus \{K_{1,t}\}$. For $t\ge 2$, we present a $\frac{t}{t+1}$-approximation algorithm for the $T\setminus t$-star packing problem that runs in $\mathcal{O}(mn^{1/2})$ time, where $n$ is the number of vertices and $m$ the number of edges of the input graph. We also design a $\frac{1}{2}$-approximation algorithm for the $2^+$-star packing problem that runs in $\mathcal{O}(m)$ time, where $m$ is the number of edges of the input graph. As a consequence, every connected graph with at least $3$ vertices has a $2^+$-star packing that covers at least half of its vertices.

2000 ◽  
Vol 11 (03) ◽  
pp. 365-371 ◽  
Author(s):  
LJUBOMIR PERKOVIĆ ◽  
BRUCE REED

We present a modification of Bodlaender's linear time algorithm that, for constant k, determine whether an input graph G has treewidth k and, if so, constructs a tree decomposition of G of width at most k. Our algorithm has the following additional feature: if G has treewidth greater than k then a subgraph G′ of G of treewidth greater than k is returned along with a tree decomposition of G′ of width at most 2k. A consequence is that the fundamental disjoint rooted paths problem can now be solved in O(n2) time. This is the primary motivation of this paper.


Algorithms ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 87 ◽  
Author(s):  
Frank Gurski ◽  
Dominique Komander ◽  
Carolin Rehs

Coloring is one of the most famous problems in graph theory. The coloring problem on undirected graphs has been well studied, whereas there are very few results for coloring problems on directed graphs. An oriented k-coloring of an oriented graph G = ( V , A ) is a partition of the vertex set V into k independent sets such that all the arcs linking two of these subsets have the same direction. The oriented chromatic number of an oriented graph G is the smallest k such that G allows an oriented k-coloring. Deciding whether an acyclic digraph allows an oriented 4-coloring is NP-hard. It follows that finding the chromatic number of an oriented graph is an NP-hard problem, too. This motivates to consider the problem on oriented co-graphs. After giving several characterizations for this graph class, we show a linear time algorithm which computes an optimal oriented coloring for an oriented co-graph. We further prove how the oriented chromatic number can be computed for the disjoint union and order composition from the oriented chromatic number of the involved oriented co-graphs. It turns out that within oriented co-graphs the oriented chromatic number is equal to the length of a longest oriented path plus one. We also show that the graph isomorphism problem on oriented co-graphs can be solved in linear time.


2019 ◽  
Vol 29 (02) ◽  
pp. 161-187
Author(s):  
Joachim Gudmundsson ◽  
Majid Mirzanezhad ◽  
Ali Mohades ◽  
Carola Wenk

Computing the Fréchet distance between two polygonal curves takes roughly quadratic time. In this paper, we show that for a special class of curves the Fréchet distance computations become easier. Let [Formula: see text] and [Formula: see text] be two polygonal curves in [Formula: see text] with [Formula: see text] and [Formula: see text] vertices, respectively. We prove four results for the case when all edges of both curves are long compared to the Fréchet distance between them: (1) a linear-time algorithm for deciding the Fréchet distance between two curves, (2) an algorithm that computes the Fréchet distance in [Formula: see text] time, (3) a linear-time [Formula: see text]-approximation algorithm, and (4) a data structure that supports [Formula: see text]-time decision queries, where [Formula: see text] is the number of vertices of the query curve and [Formula: see text] the number of vertices of the preprocessed curve.


2021 ◽  
Author(s):  
Cristina G. Fernandes ◽  
Carla N. Lintzmayer ◽  
Mário César San Felice

We denote by Maximum Leaf Spanning k-Forest the problem of, given a positive integer k and a graph G with at most k components, finding a spanning forest in G with at most k components and the maximum number of leaves. A leaf in a forest is defined as a vertex of degree at most one. The case k = 1 for connected graphs is known to be NP-hard, and is well studied in the literature, with the best approximation algorithm proposed more than 20 years ago by Solis-Oba. The best known approximation algorithm for Maximum Leaf Spanning k-Forest with a slightly different leaf definition is a 3-approximation based on an approach by Lu and Ravi for the k = 1 case. We extend the algorithm of Solis-Oba to achieve a 2-approximation for Maximum Leaf Spanning k-Forest.


2014 ◽  
Vol 2014 ◽  
pp. 1-13
Author(s):  
Peiqiang Liu ◽  
Daming Zhu ◽  
Jinjie Xiao ◽  
Qingsong Xie ◽  
Yanyan Mao

A biclustering problem consists of objects and an attribute vector for each object. Biclustering aims at finding a bicluster—a subset of objects that exhibit similar behavior across a subset of attributes, or vice versa. Biclustering in matrices with binary entries (“0”/“1”) can be simplified into the problem of finding submatrices with entries of “1.” In this paper, we consider a variant of the biclustering problem: thek-submatrix partition of binary matrices problem. The input of the problem contains ann×mmatrix with entries (“0”/“1”) and a constant positive integerk. Thek-submatrix partition of binary matrices problem is to find exactlyksubmatrices with entries of “1” such that theseksubmatrices are pairwise row and column exclusive and each row (column) in the matrix occurs in exactly one of theksubmatrices. We discuss the complexity of thek-submatrix partition of binary matrices problem and show that the problem is NP-hard for anyk≥3by reduction from a biclustering problem in bipartite graphs.


2014 ◽  
Vol 24 (03) ◽  
pp. 225-236 ◽  
Author(s):  
DAVID KIRKPATRICK ◽  
BOTING YANG ◽  
SANDRA ZILLES

Given an arrangement A of n sensors and two points s and t in the plane, the barrier resilience of A with respect to s and t is the minimum number of sensors whose removal permits a path from s to t such that the path does not intersect the coverage region of any sensor in A. When the surveillance domain is the entire plane and sensor coverage regions are unit line segments, even with restricted orientations, the problem of determining the barrier resilience is known to be NP-hard. On the other hand, if sensor coverage regions are arbitrary lines, the problem has a trivial linear time solution. In this paper, we study the case where each sensor coverage region is an arbitrary ray, and give an O(n2m) time algorithm for computing the barrier resilience when there are m ⩾ 1 sensor intersections.


Mathematics ◽  
2021 ◽  
Vol 9 (14) ◽  
pp. 1592
Author(s):  
Iztok Peterin ◽  
Gabriel Semanišin

A shortest path P of a graph G is maximal if P is not contained as a subpath in any other shortest path. A set S⊆V(G) is a maximal shortest paths cover if every maximal shortest path of G contains a vertex of S. The minimum cardinality of a maximal shortest paths cover is called the maximal shortest paths cover number and is denoted by ξ(G). We show that it is NP-hard to determine ξ(G). We establish a connection between ξ(G) and several other graph parameters. We present a linear time algorithm that computes exact value for ξ(T) of a tree T.


2005 ◽  
Vol DMTCS Proceedings vol. AE,... (Proceedings) ◽  
Author(s):  
Adrian Kosowski ◽  
Michal Malafiejski ◽  
Pawel Zyliński

International audience In our paper we consider the $P_3$-packing problem in subcubic graphs of different connectivity, improving earlier results of Kelmans and Mubayi. We show that there exists a $P_3$-packing of at least $\lceil 3n/4\rceil$ vertices in any connected subcubic graph of order $n>5$ and minimum vertex degree $\delta \geq 2$, and that this bound is tight. The proof is constructive and implied by a linear-time algorithm. We use this result to show that any $2$-connected cubic graph of order $n>8$ has a $P_3$-packing of at least $\lceil 7n/9 \rceil$ vertices.


Sign in / Sign up

Export Citation Format

Share Document