scholarly journals A Note on $\mathtt{V}$-free 2-matchings

10.37236/5258 ◽  
2016 ◽  
Vol 23 (4) ◽  
Author(s):  
Kristóf Bérczi ◽  
Attila Bernáth ◽  
Máté Vizer
Keyword(s):  
Bipartite Graph ◽  
Packing Problem ◽  
Bipartite Graphs ◽  
Matching Problem ◽  
Hypergraph Matching ◽  
Path Packing ◽  
Np Complete

Motivated by a conjecture of Liang, we introduce a restricted path packing problem in bipartite graphs that we call a $\mathtt{V}$-free $2$-matching. We verify the conjecture through a weakening of the hypergraph matching problem. We close the paper by showing that it is NP-complete to decide whether one of the color classes of a bipartite graph can be covered by a $\mathtt{V}$-free $2$-matching.

scholarly journals On the induced matching problem in hamiltonian bipartite graphs

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Yinglei Song
Keyword(s):  
Bipartite Graph ◽  
Parameterized Complexity ◽  
Bipartite Graphs ◽  
Matching Problem ◽  
Induced Matching ◽  
Subexponential Time ◽  
Maximum Induced Matching

Abstract In this paper, we study the parameterized complexity of the induced matching problem in hamiltonian bipartite graphs and the inapproximability of the maximum induced matching problem in hamiltonian bipartite graphs. We show that, given a hamiltonian bipartite graph, the induced matching problem is W[1]-hard and cannot be solved in time n o ⁢ ( k ) {n^{o(\sqrt{k})}} , where n is the number of vertices in the graph, unless the 3SAT problem can be solved in subexponential time. In addition, we show that unless NP = P {\operatorname{NP}=\operatorname{P}} , a maximum induced matching in a hamiltonian bipartite graph cannot be approximated within a ratio of n 1 / 4 - ϵ {n^{1/4-\epsilon}} , where n is the number of vertices in the graph.

scholarly journals Detection number of bipartite graphs and cubic graphs

2014 ◽  
Vol Vol. 16 no. 3 ◽  
Author(s):  
Frederic Havet ◽  
Nagarajan Paramaguru ◽  
Rathinaswamy Sampathkumar
Keyword(s):  
Positive Integer ◽  
Bipartite Graph ◽  
Connected Graph ◽  
Minimum Degree ◽  
Bipartite Graphs ◽  
Sufficient Condition ◽  
Cubic Graphs ◽  
Cubic Graph ◽  
International Audience ◽  
Np Complete

International audience For a connected graph G of order |V(G)| ≥3 and a k-labelling c : E(G) →{1,2,…,k} of the edges of G, the code of a vertex v of G is the ordered k-tuple (ℓ1,ℓ2,…,ℓk), where ℓi is the number of edges incident with v that are labelled i. The k-labelling c is detectable if every two adjacent vertices of G have distinct codes. The minimum positive integer k for which G has a detectable k-labelling is the detection number det(G) of G. In this paper, we show that it is NP-complete to decide if the detection number of a cubic graph is 2. We also show that the detection number of every bipartite graph of minimum degree at least 3 is at most 2. Finally, we give some sufficient condition for a cubic graph to have detection number 3.

Augmenting trail theorem for the maximum 1-2 matching problem

2017 ◽  
Vol 09 (04) ◽  
pp. 1750056 ◽  
Author(s):  
Hiroki Izumi ◽  
Sennosuke Watanabe ◽  
Yoshihide Watanabe
Keyword(s):  
Bipartite Graph ◽  
Bipartite Graphs ◽  
Matching Problem ◽  
Matching Problems ◽  
Augmenting Path

We consider the maximum 1-2 matching problem in bipartite graphs. The notion of the augmenting trail for the 1-2 matching problem, which is the extension of the notion of the augmenting path for the 1-1 matching problem is introduced. The main purpose of the present paper is to prove “the augmenting trail theorem” for the 1-2 matching problem in the bipartite graph, which is an analogue of the augmenting path theorem by Bergé for the usual 1-1 matching problems.

scholarly journals An O(n^3) time algorithm for the maximum weight b-matching problem on bipartite graphs

2020 ◽  
Author(s):  
Fatemeh Rajabi-Alni ◽  
Alireza Bagheri ◽  
Behrouz Minaei-Bidgoli
Keyword(s):  
Computational Biology ◽  
Bipartite Graph ◽  
Association Studies ◽  
Time Algorithm ◽  
Bipartite Graphs ◽  
Maximum Weight ◽  
Positive Real ◽  
Matching Problem ◽  
Genome Wide ◽  
Integer Weight

Abstract Background: A matching between two sets A and B assigns some elements of A to some elements of B. Finding the similarity between two sets of elements by advantage of the matching is widely used in computational biology for example in the contexts of genome-wide and sequencing association studies. Frequently, the capacities of the elements are limited. That is, the number of the elements that can be matched to each element should not exceed a given number. Results: We use bipartite graphs to model relationships between pairs of objects. Given an undirected bipartite graph G = (A [ B;E), the b-matching of G matches each vertex v in A (resp. B) to at least 1 and at most b(v) vertices in B (resp. A), where b(v) denotes the capacity of v. We propose the rst O(n3) time algorithm for nding the maximum weight b-matching of G, where jAj + jBj = O(n). Conclusions: The b-matching has been studied widely for the bipartite graphs with integer weight edges. But our algorithm is the rst algorithm for the maximum (respectively minimum) b-matching problem with non positive real (respectively non negative real) edge weights.

scholarly journals An O(n3) time algorithm for the maximum weight b-matching problem on bipartite graphs

2020 ◽  
Author(s):  
Fatemeh Rajabi-Alni ◽  
Alireza Bagheri ◽  
Behrouz Minaei-Bidgoli
Keyword(s):  
Computational Biology ◽  
Bipartite Graph ◽  
Association Studies ◽  
Time Algorithm ◽  
Bipartite Graphs ◽  
Maximum Weight ◽  
Positive Real ◽  
Matching Problem ◽  
Genome Wide ◽  
Integer Weight

Abstract Background: A matching between two sets A and B assigns some elements of A to some elements of B. Finding the similarity between two sets of elements by advantage of the matching is widely used in computational biology for example in the contexts of genome-wide and sequencing association studies. Frequently, the capacities of the elements are limited. That is, the number of the elements that can be matched to each element should not exceed a given number. Results: We use bipartite graphs to model relationships between pairs of objects. Given an undirected bipartite graph G = (A∪B,E), the b-matching of G matches each vertex v in A (resp. B) to at least 1 and at most b(v) vertices in B (resp. A), where b(v) denotes the capacity of v. We propose the first O(n3) time algorithm for finding the maximum weight b-matching of G, where |A|+|B| = O(n). Conclusions: The b-matching has been studied widely for the bipartite graphs with integer weight edges. But our algorithm is the first algorithm for the maximum (respectively minimum) b-matching problem with non positive real (respectively non negative real) edge weights.

ON LOCALLY-BALANCED 2-PARTITIONS OF BIPARTITE GRAPHS

2020 ◽  
Vol 54 (3 (253)) ◽  
pp. 137-145
Author(s):  
Aram H. Gharibyan ◽  
Petros A. Petrosyan
Keyword(s):  
Bipartite Graph ◽  
Open Neighborhood ◽  
Bipartite Graphs ◽  
The Other ◽  
Open Neighbourhood ◽  
Np Complete ◽  
Convex Bipartite Graphs

A \emph{$2$-partition of a graph $G$} is a function $f:V(G)\rightarrow \{0,1\}$. A $2$-partition $f$ of a graph $G$ is a \emph{locally-balanced with an open neighborhood}, if for every $v\in V(G)$, $\left\vert \vert \{u\in N_{G}(v)\colon\,f(u)=0\}\vert - \vert \{u\in N_{G}(v)\colon\,f(u)=1\}\vert \right\vert\leq 1$. A bipartite graph is \emph{$(a,b)$-biregular} if all vertices in one part have degree $a$ and all vertices in the other part have degree $b$. In this paper we prove that the problem of deciding, if a given graph has a locally-balanced $2$-partition with an open neighborhood is $NP$-complete even for $(3,8)$-biregular bipartite graphs. We also prove that a $(2,2k+1)$-biregular bipartite graph has a locally-balanced $2$-partition with an open neighbourhood if and only if it has no cycle of length $2 \pmod{4}$. Next, we prove that if $G$ is a subcubic bipartite graph that has no cycle of length $2 \pmod{4}$, then $G$ has a locally-balanced $2$-partition with an open neighbourhood. Finally, we show that all doubly convex bipartite graphs have a locally-balanced $2$-partition with an open neighbourhood.

ACYCLIC MATCHINGS IN SUBCLASSES OF BIPARTITE GRAPHS

2012 ◽  
Vol 04 (04) ◽  
pp. 1250050 ◽  
Author(s):  
B. S. PANDA ◽  
D. PRADHAN
Keyword(s):  
Time Algorithm ◽  
Bipartite Graphs ◽  
Maximum Cardinality ◽  
Chain Graph ◽  
Matching Problem ◽  
Permutation Graph ◽  
Complexity Result ◽  
Np Complete ◽  
A Chain ◽  
Acyclic Matching

A set M ⊆ E is called an acyclic matching of a graph G = (V, E) if no two edges in M are adjacent and the subgraph induced by the set of end vertices of the edges of M is acyclic. Given a positive integer k and a graph G = (V, E), the acyclic matching problem is to decide whether G has an acyclic matching of cardinality at least k. Goddard et al. (Discrete Math.293(1–3) (2005) 129–138) introduced the concept of the acyclic matching problem and proved that the acyclic matching problem is NP-complete for general graphs. In this paper, we propose an O(n + m) time algorithm to find a maximum cardinality acyclic matching in a chain graph having n vertices and m edges and obtain an expression for the number of maximum cardinality acyclic matchings in a chain graph. We also propose a dynamic programming-based O(n + m) time algorithm to find a maximum cardinality acyclic matching in a bipartite permutation graph having n vertices and m edges. Finally, we strengthen the complexity result of the acyclic matching problem by showing that this problem remains NP-complete for perfect elimination bipartite graphs.

scholarly journals The Edmonds-Gallai Decomposition for the $k$-Piece Packing Problem

10.37236/1905 ◽  
2005 ◽  
Vol 12 (1) ◽  
Author(s):  
Marek Janata ◽  
Martin Loebl ◽  
Jácint Szabó
Keyword(s):  
Polynomial Algorithm ◽  
Undirected Graph ◽  
Packing Problem ◽  
Matching Problem ◽  
Graph Packing ◽  
Path Packing ◽  
New Type ◽  
Vertex Sets ◽  
Simple Connected Graph ◽  
Type Decomposition

Generalizing Kaneko's long path packing problem, Hartvigsen, Hell and Szabó consider a new type of undirected graph packing problem, called the $k$-piece packing problem. A $k$-piece is a simple, connected graph with highest degree exactly $k$ so in the case $k=1$ we get the classical matching problem. They give a polynomial algorithm, a Tutte-type characterization and a Berge-type minimax formula for the $k$-piece packing problem. However, they leave open the question of an Edmonds-Gallai type decomposition. This paper fills this gap by describing such a decomposition. We also prove that the vertex sets coverable by $k$-piece packings have a certain matroidal structure.

scholarly journals Partitioning to three matchings of given size is NP-complete for bipartite graphs

2014 ◽  
Vol 6 (2) ◽  
pp. 206-209 ◽  
Author(s):  
Dömötör Pálvölgyi
Keyword(s):  
Bipartite Graph ◽  
Maximum Degree ◽  
Perfect Matching ◽  
Bipartite Graphs ◽  
Simple Graph ◽  
Np Complete

Abstract We show that the problem of deciding whether the edge set of a bipartite graph can be partitioned into three matchings, of size k1, k2 and k3 is NP-complete, even if one of the matchings is required to be perfect. We also show that the problem of deciding whether the edge set of a simple graph contains a perfect matching and a disjoint matching of size k or not is NP-complete, already for bipartite graphs with maximum degree 3. It also follows from our construction that it is NP-complete to decide whether in a bipartite graph there is a perfect matching and a disjoint matching that covers all vertices whose degree is at least 2.

Reconstructing a Graph from its Neighborhood Lists

1993 ◽  
Vol 2 (2) ◽  
pp. 103-113 ◽  
Author(s):  
Martin Aigner ◽  
Eberhard Triesch
Keyword(s):  
Decision Problem ◽  
Graph Isomorphism ◽  
Bipartite Graphs ◽  
Labeled Graph ◽  
Np Complete

Associate to a finite labeled graph G(V, E) its multiset of neighborhoods (G) = {N(υ): υ ∈ V}. We discuss the question of when a list is realizable by a graph, and to what extent G is determined by (G). The main results are: the decision problem is NP-complete; for bipartite graphs the decision problem is polynomially equivalent to Graph Isomorphism; forests G are determined up to isomorphism by (G); and if G is connected bipartite and (H) = (G), then H is completely described.

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