13 research outputs found

    On minimum tt-claw deletion in split graphs

    Full text link
    For t3t\geq 3, K1,tK_{1, t} is called tt-claw. In minimum tt-claw deletion problem (\texttt{Min-tt-Claw-Del}), given a graph G=(V,E)G=(V, E), it is required to find a vertex set SS of minimum size such that G[VS]G[V\setminus S] is tt-claw free. In a split graph, the vertex set is partitioned into two sets such that one forms a clique and the other forms an independent set. Every tt-claw in a split graph has a center vertex in the clique partition. This observation motivates us to consider the minimum one-sided bipartite tt-claw deletion problem (\texttt{Min-tt-OSBCD}). Given a bipartite graph G=(AB,E)G=(A \cup B, E), in \texttt{Min-tt-OSBCD} it is asked to find a vertex set SS of minimum size such that G[VS]G[V \setminus S] has no tt-claw with the center vertex in AA. A primal-dual algorithm approximates \texttt{Min-tt-OSBCD} within a factor of tt. We prove that it is \UGC-hard to approximate with a factor better than tt. We also prove it is approximable within a factor of 2 for dense bipartite graphs. By using these results on \texttt{Min-tt-OSBCD}, we prove that \texttt{Min-tt-Claw-Del} is \UGC-hard to approximate within a factor better than tt, for split graphs. We also consider their complementary maximization problems and prove that they are \APX-complete.Comment: 11 pages and 1 figur

    On the Complexity of Making a Distinguished Vertex Minimum or Maximum Degree by Vertex Deletion

    Full text link
    In this paper, we investigate the approximability of two node deletion problems. Given a vertex weighted graph G=(V,E)G=(V,E) and a specified, or "distinguished" vertex pVp \in V, MDD(min) is the problem of finding a minimum weight vertex set SV{p}S \subseteq V\setminus \{p\} such that pp becomes the minimum degree vertex in G[VS]G[V \setminus S]; and MDD(max) is the problem of finding a minimum weight vertex set SV{p}S \subseteq V\setminus \{p\} such that pp becomes the maximum degree vertex in G[VS]G[V \setminus S]. These are known NPNP-complete problems and have been studied from the parameterized complexity point of view in previous work. Here, we prove that for any ϵ>0\epsilon > 0, both the problems cannot be approximated within a factor (1ϵ)logn(1 - \epsilon)\log n, unless NPDTIME(nloglogn)NP \subseteq DTIME(n^{\log\log n}). We also show that for any ϵ>0\epsilon > 0, MDD(min) cannot be approximated within a factor (1ϵ)logn(1 -\epsilon)\log n on bipartite graphs, unless NPDTIME(nloglogn)NP \subseteq DTIME(n^{\log\log n}), and that for any ϵ>0\epsilon > 0, MDD(max) cannot be approximated within a factor (1/2ϵ)logn(1/2 - \epsilon)\log n on bipartite graphs, unless NPDTIME(nloglogn)NP \subseteq DTIME(n^{\log\log n}). We give an O(logn)O(\log n) factor approximation algorithm for MDD(max) on general graphs, provided the degree of pp is O(logn)O(\log n). We then show that if the degree of pp is nO(logn)n-O(\log n), a similar result holds for MDD(min). We prove that MDD(max) is APXAPX-complete on 3-regular unweighted graphs and provide an approximation algorithm with ratio 1.5831.583 when GG is a 3-regular unweighted graph. In addition, we show that MDD(min) can be solved in polynomial time when GG is a regular graph of constant degree.Comment: 16 pages, 4 figures, submitted to Elsevier's Journal of Discrete Algorithm

    On the Complexity of Co-secure Dominating Set Problem

    Full text link
    A set DVD \subseteq V of a graph G=(V,E)G=(V, E) is a dominating set of GG if every vertex vVDv\in V\setminus D is adjacent to at least one vertex in D.D. A set SVS \subseteq V is a co-secure dominating set (CSDS) of a graph GG if SS is a dominating set of GG and for each vertex uSu \in S there exists a vertex vVSv \in V\setminus S such that uvEuv \in E and (S{u}){v}(S\setminus \{u\}) \cup \{v\} is a dominating set of GG. The minimum cardinality of a co-secure dominating set of GG is the co-secure domination number and it is denoted by γcs(G)\gamma_{cs}(G). Given a graph G=(V,E)G=(V, E), the minimum co-secure dominating set problem (Min Co-secure Dom) is to find a co-secure dominating set of minimum cardinality. In this paper, we strengthen the inapproximability result of Min Co-secure Dom for general graphs by showing that this problem can not be approximated within a factor of (1ϵ)lnV(1- \epsilon)\ln |V| for perfect elimination bipartite graphs and star convex bipartite graphs unless P=NP. On the positive side, we show that Min Co-secure Dom can be approximated within a factor of O(lnV)O(\ln |V|) for any graph GG with δ(G)2\delta(G)\geq 2. For 33-regular and 44-regular graphs, we show that Min Co-secure Dom is approximable within a factor of 83\dfrac{8}{3} and 103\dfrac{10}{3}, respectively. Furthermore, we prove that Min Co-secure Dom is APX-complete for 33-regular graphs.Comment: 12 pages, 2 figure

    The Complexity of Finding Subgraphs Whose Matching Number Equals the Vertex Cover Number

    No full text
    The class of graphs where the size of a minimum vertex cover equals that of a maximum matching is known as König-Egerváry graphs. König-Egerváry graphs have been studied extensively from a graph theoretic point of view. In this paper, we introduce and study the algorithmic complexity of finding maximum König-Egerváry subgraphs of a given graph. More specifically, we look at the problem of finding a minimum number of vertices or edges to delete to make the resulting graph König-Egerváry. We show that both these versions are NP-complete and study their complexity from the points of view of approximation and parameterized complexity. En route, we point out an interesting connection between the vertex deletion version and the Above Guarantee Vertex Cover problem where one is interested in the parameterized complexity of the Vertex Cover problem when parameterized by the ‘additional number of vertices ’ needed beyond the matching size. This connection is of independent interest and could be useful in establishing the parameterized complexity of Above Guarantee Vertex Cover problem

    The Complexity of König Subgraph Problems and Above-Guarantee Vertex Cover

    No full text
    A graph is König-Egerváry if the size of a minimum vertex cover equals that of a maximum matching in the graph. These graphs have been studied extensively from a graph-theoretic point of view. In this paper, we introduce and study the algorithmic complexity of finding König-Egerváry subgraphs of a given graph. In particular, given a graph G and a nonnegative integer k, we are interested in the following questions: 1. does there exist a set of k vertices (edges) whose deletion makes the graph König-Egerváry? 2. does there exist a set of k vertices (edges) that induce a König-Egerváry subgraph? We show that these problems are NP-complete and study their complexity from the points of view of approximation and parameterized complexity. Towards this end, we first study the algorithmic complexity of Above Guarantee Vertex Cover, where one is interested in minimizing the additional number of vertices needed beyond the maximum matching size for the vertex cover. Further, while studying the parameterized complexity of the problem of deleting k vertices to obtain a König-Egerváry graph, we show a number of interesting structural results on matchings and vertex covers which could be useful in other contexts
    corecore