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1

Edge Forcing in Butterfly Networks

Jessy Sujana G, Rajasingh Indra, Rajalaxmi T.M., Rajan R. Sundara

Fundamenta Informaticae

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2021

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Vol. 182, nr 3

285--299

EN

A zero forcing set is a set S of vertices of a graph G, called forced vertices of G, which are able to force the entire graph by applying the following process iteratively: At any particular instance of time, if any forced vertex has a unique unforced neighbor, it forces that neighbor. In this paper, we introduce a variant of zero forcing set that induces independent edges and name it as edge-forcing set. The minimum cardinality of an edge-forcing set is called the edge-forcing number. We prove that the edge-forcing problem of determining the edge-forcing number is NP-complete. Further, we study the edge-forcing number of butterfly networks. We obtain a lower bound on the edge-forcing number of butterfly networks and prove that this bound is tight for butterfly networks of dimensions 2, 3, 4 and 5 and obtain an upper bound for the higher dimensions.

2

The hardness of the independence and matching clutter of a graph

Hambardzumyan S., Mkrtchyan V. V., Musoyan V. L., Sargsyan H.

Opuscula Mathematica

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2016

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Vol. 36, no. 3

375--397

EN

A clutter (or antichain or Sperner family) L is a pair (V, E), where V is a finite set and E is a family of subsets of V none of which is a subset of another. Usually, the elements of V are called vertices of L, and the elements of E are called edges of L. A subset se of an edge e of a clutter is called recognizing for e, if se is not a subset of another edge. The hardness of an edge e of a clutter is the ratio of the size of e's smallest recognizing subset to the size of e. The hardness of a clutter is the maximum hardness of its edges. We study the hardness of clutters arising from independent sets and matchings of graphs.

3

A new and fast approximation algorithm for vertex cover using a maximum independent set (VCUMI)

Khan I., Riaz N.

Operations Research and Decisions

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2015

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Vol. 25, No. 4

5--18

EN

The importance of non-deterministic polynomial (NP) problems in real world scenarios has compelled researchers to consider simple ways of finding approximate solutions to these problems in polynomial time. Minimum vertex cover is an NP complete problem, where the objective is to cover all the edges in a graph with the minimal number of vertices possible. The maximal independent set and maximal clique problems also belong to the same class. An important property that we have analyzed while considering various approaches to find approximate solutions to the minimum vertex cover problem (MVC) is that solving MVC directly can result in a bigger error ratio. We propose a new approximation algorithm for the minimum vertex cover problem called vertex cover using a maximum independent set (VCUMI). This algorithm works by removing the nodes of a maximum independent set until the graph is an approximate solution of MVC. Based on empirical results, it can be stated that VCUMI outperforms all competing algorithms presented in the literature. Based on all the benchmarks used, VCUMI achieved the worst case error ratio of 1.033, while VSA, MDG and NOVAC-1 gave the worst error ratios of 1.583, 1.107 and 1.04, respectively.

4

On equality in an upper bound for the acyclic domination number

Samodivkin V.

Opuscula Mathematica

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2008

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Vol. 28, no. 3

331-334

EN

A subset A of vertices in a graph G is acyclic if the subgraph it induces contains no cycles. The acyclic domination number ϒa (G) of a graph G is the minimum cardinality of an acyclic dominating set of G. For any graph G with n vertices and maximum degree Δ(G), ϒa(G) ≤ n - Δ(G). In this paper we characterize the connected graphs and the connected triangle-free graphs which achieve this upper bound.

5

Independent set dominanting sets in bipartite graphs

Zelinka B.

Opuscula Mathematica

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2005

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Vol. 25, no. 2

345-349

EN

The paper continues the study of independent set dominating sets in graphs which was started by E. Sampathkumar. A subset D of the vertex set V(G) of a graph G is called a set dominating set (shortly sd-set) in G, if for each set X ikkeq V(G) - D there exists a set Y ikkeq D such that the subgraph of G induced X cup Y is connected. The minimum number of vertices of an sd-set in G is called the set domination number gammas (G) of G. An sd-set D in G such that /D/ = gammas(G) is called a gammas-set in G. In this paper we study sd-sets in bipartite graphs which are simultaneously independent. We apply the theory of hypergraphs.